fix ref

### MCP Server Enhancement:
- Add 3 new card-related MCP tools: get_user_cards, draw_card, get_draw_status
- Fix ServiceClient missing methods for ai.card API integration
- Total MCP tools now: 20 (including card functionality)

### ServiceClient Fixes:
- Add get_user_cards() method for card collection retrieval
- Add draw_card() method for gacha functionality
- Fix JSON Value handling in card count display

### Integration Success:
- ai.gpt MCP server successfully starts with all 20 tools
- HTTP endpoints properly handle card-related requests
- Ready for ai.card server connection on port 8000

🤖 Generated with [Claude Code](https://claude.ai/code)

Co-Authored-By: Claude <noreply@anthropic.com>

.gitignore

@@ -1,7 +1,24 @@
-**target
+# Rust
-**.lock
+target/
-output.json
+Cargo.lock
-config/*.db
+
-aigpt
+# Database files
-mcp/scripts/__*
+*.db
-data
+*.db-shm
+*.db-wal
+
+# IDE
+.idea/
+.vscode/
+*.swp
+*.swo
+
+# OS
+.DS_Store
+Thumbs.db
+
+# Logs
+*.log
+json
+gpt
+.claude

Cargo.toml

@@ -2,12 +2,47 @@
 name = "aigpt"
 version = "0.1.0"
 edition = "2021"
+authors = ["syui"]
+description = "Simple memory storage for Claude with MCP"
+
+
+[[bin]]
+name = "aigpt"
+path = "src/main.rs"
+
+[[bin]]
+name = "memory-mcp"
+path = "src/bin/mcp_server.rs"
+
+[[bin]]
+name = "memory-mcp-extended"
+path = "src/bin/mcp_server_extended.rs"
 
 [dependencies]
-reqwest = { version = "*", features = ["json"] }
+# CLI and async
-serde = { version = "*", features = ["derive"] }
+clap = { version = "4.5", features = ["derive"] }
-serde_json = "*"
+tokio = { version = "1.40", features = ["full"] }
-tokio = { version = "*", features = ["full"] }
+
-clap = { version = "*", features = ["derive"] }
+# JSON and serialization
-shellexpand = "*"
+serde = { version = "1.0", features = ["derive"] }
-fs_extra = "*"
+serde_json = "1.0"
+
+# Date/time and UUID
+chrono = { version = "0.4", features = ["serde"] }
+uuid = { version = "1.10", features = ["v4"] }
+
+# Error handling and utilities
+anyhow = "1.0"
+dirs = "5.0"
+
+# Extended features (optional)
+reqwest = { version = "0.11", features = ["json"], optional = true }
+scraper = { version = "0.18", optional = true }
+openai = { version = "1.1", optional = true }
+
+[features]
+default = []
+extended = ["semantic-search", "ai-analysis", "web-integration"]
+semantic-search = ["openai"]
+ai-analysis = ["openai"] 
+web-integration = ["reqwest", "scraper"]

README.md

@@ -0,0 +1,177 @@
+# aigpt - Claude Memory MCP Server
+
+ChatGPTのメモリ機能を参考にした、Claude Desktop/Code用のシンプルなメモリストレージシステムです。
+
+## 機能
+
+- **メモリのCRUD操作**: メモリの作成、更新、削除、検索
+- **ChatGPT JSONインポート**: ChatGPTの会話履歴からメモリを抽出
+- **stdio MCP実装**: Claude Desktop/Codeとの簡潔な連携
+- **JSONファイル保存**: シンプルなファイルベースのデータ保存
+
+## インストール
+
+1. Rustをインストール（まだの場合）:
+```bash
+curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh
+```
+
+2. プロジェクトをビルド:
+```bash
+cargo build --release
+```
+
+3. バイナリをパスの通った場所にコピー（オプション）:
+```bash
+cp target/release/aigpt $HOME/.cargo/bin/
+```
+
+4. Claude Code/Desktopに追加
+
+```sh
+# Claude Codeの場合
+claude mcp add aigpt $HOME/.cargo/bin/aigpt server
+
+# または
+claude mcp add aigpt $HOME/.cargo/bin/aigpt serve
+```
+
+## 使用方法
+
+### ヘルプの表示
+```bash
+aigpt --help
+```
+
+### MCPサーバーとして起動
+```bash
+# MCPサーバー起動 (どちらでも可)
+aigpt server
+aigpt serve
+```
+
+### ChatGPT会話のインポート
+```bash
+# ChatGPT conversations.jsonをインポート
+aigpt import path/to/conversations.json
+```
+
+## Claude Desktop/Codeへの設定
+
+1. Claude Desktopの設定ファイルを開く:
+   - macOS: `~/Library/Application Support/Claude/claude_desktop_config.json`
+   - Windows: `%APPDATA%\Claude\claude_desktop_config.json`
+   - Linux: `~/.config/Claude/claude_desktop_config.json`
+
+2. 以下の設定を追加:
+```json
+{
+  "mcpServers": {
+    "aigpt": {
+      "command": "/Users/syui/.cargo/bin/aigpt",
+      "args": ["server"]
+    }
+  }
+}
+```
+
+## 提供するMCPツール一覧
+
+1. **create_memory** - 新しいメモリを作成
+2. **update_memory** - 既存のメモリを更新
+3. **delete_memory** - メモリを削除
+4. **search_memories** - メモリを検索
+5. **list_conversations** - インポートされた会話を一覧表示
+
+## ツールの使用例
+
+Claude Desktop/Codeで以下のように使用します：
+
+### メモリの作成
+```
+MCPツールを使って「今日は良い天気です」というメモリーを作成してください
+```
+
+### メモリの検索
+```
+MCPツールを使って「天気」に関するメモリーを検索してください
+```
+
+### 会話一覧の表示
+```
+MCPツールを使ってインポートした会話の一覧を表示してください
+```
+
+## データ保存
+
+- デフォルトパス: `~/.config/syui/ai/gpt/memory.json`
+- JSONファイルでデータを保存
+- 自動的にディレクトリとファイルを作成
+
+### データ構造
+
+```json
+{
+  "memories": {
+    "uuid": {
+      "id": "uuid",
+      "content": "メモリーの内容",
+      "created_at": "2024-01-01T00:00:00Z",
+      "updated_at": "2024-01-01T00:00:00Z"
+    }
+  },
+  "conversations": {
+    "conversation_id": {
+      "id": "conversation_id",
+      "title": "会話のタイトル",
+      "created_at": "2024-01-01T00:00:00Z",
+      "message_count": 10
+    }
+  }
+}
+```
+
+## 開発
+
+```bash
+# 開発モードで実行
+cargo run -- server
+
+# ChatGPTインポートのテスト
+cargo run -- import json/conversations.json
+
+# テストの実行
+cargo test
+
+# フォーマット
+cargo fmt
+
+# Lintチェック
+cargo clippy
+```
+
+## トラブルシューティング
+
+### MCPサーバーが起動しない
+```bash
+# バイナリが存在するか確認
+ls -la ~/.cargo/bin/aigpt
+
+# 手動でテスト
+echo '{"jsonrpc": "2.0", "method": "tools/list", "id": 1}' | aigpt server
+```
+
+### Claude Desktopでツールが見つからない
+1. Claude Desktopを完全に再起動
+2. 設定ファイルのパスが正しいか確認
+3. ログファイルを確認: `~/Library/Logs/Claude/mcp-server-aigpt.log`
+
+### インポートが失敗する
+```bash
+# JSONファイルの形式を確認
+head -100 conversations.json | jq '.[0] | keys'
+```
+
+## ライセンス
+
+MIT

claude.md

@@ -0,0 +1,95 @@
+# claude用の記憶装置を作る
+
+claude desktop, claude codeで使用できるmemory機能をmcpで作ります。
+
+1. chatgptのメモリ機能を参考に
+2. chatgptのjsonをimportできる @json/
+3. rustで作る
+
+## 自動実行設定
+```json
+{
+  "mcp_auto_execute": true,
+  "memory_auto_save": true,
+  "memory_auto_search": true,
+  "trigger_sensitivity": "high"
+}
+```
+
+## 自動メモリー保存のルール（強化版）
+
+**即座に自動実行** - 以下の情報が会話に現れた瞬間、create_memory MCPツールを自動実行：
+
+### 1. **ユーザーの個人情報**
+**トリガーワード**: 名前、誕生日、住所、年齢、職業、家族、出身
+- 基本情報: 名前、誕生日、住所、年齢、性別
+- 関係性: 家族構成、恋人、友人関係
+- 好み: 好きなもの、嫌いなもの、趣味、音楽、映画、本
+- 習慣: 日課、スケジュール、ルーティン
+- 価値観: 信念、考え方、人生観
+
+### 2. **重要な決定事項**
+**トリガーワード**: 決めた、決定、方針、計画、予定、目標
+- プロジェクト方針の決定
+- 技術選択の決定
+- 設定・環境の変更
+- 今後のロードマップ
+- 作業分担・役割
+
+### 3. **技術的な解決策**
+**トリガーワード**: 解決、修正、対処、設定、インストール、手順
+- エラーの解決方法
+- 有用なコマンド・スクリプト
+- 設定手順・インストール方法
+- デバッグテクニック
+- 最適化手法
+
+### 4. **学習・発見事項**
+**トリガーワード**: 学んだ、わかった、発見、理解、気づき
+- 新しい知識・概念の理解
+- ツール・ライブラリの使い方
+- ベストプラクティス
+- 失敗から得た教訓
+
+## 自動メモリー検索のルール（強化版）
+
+**会話開始時に自動実行** - search_memories を実行してコンテキストを取得
+
+**即座に自動実行** - 以下の場合、search_memories MCPツールを自動実行：
+
+### 1. **過去参照キーワード検出**
+**トリガーワード**: 前に、以前、昔、過去、先ほど、さっき、この間
+- 「前に話した〜」
+- 「以前設定した〜」
+- 「昔やった〜」
+
+### 2. **記憶呼び出しキーワード**
+**トリガーワード**: 覚えている、記録、メモ、保存、履歴
+- 「覚えていますか？」
+- 「記録していた〜」
+- 「メモした〜」
+
+### 3. **設定・好み確認**
+**トリガーワード**: 好み、設定、環境、構成、preferences
+- ユーザーの好みを確認する必要がある場合
+- 過去の設定を参照する必要がある場合
+- 環境構成を確認する必要がある場合
+
+### 4. **不明な参照**
+- ユーザーが具体的でない参照をした場合
+- 「あれ」「それ」「例のやつ」などの曖昧な表現
+- 文脈から過去の情報が必要と判断される場合
+
+## 自動実行タイミング
+
+1. **会話開始時**: search_memories を実行してコンテキスト取得
+2. **リアルタイム**: トリガーワード検出後、即座にMCPツール実行
+3. **会話終了時**: 重要な情報があれば create_memory で保存
+4. **定期的**: 長い会話では中間地点でメモリー整理
+
+## エラーハンドリング
+
+- MCPツールが利用できない場合は通常の会話を継続
+- メモリー保存失敗時はユーザーに通知
+- 検索結果が空の場合も適切に対応
+

docs/README_CONFIG.md

@@ -0,0 +1,125 @@
+# Claude Memory MCP 設定ガイド
+
+## モード選択
+
+### 標準モード (Simple Mode)
+- 基本的なメモリー機能のみ
+- 軽量で高速
+- 最小限の依存関係
+
+### 拡張モード (Extended Mode)  
+- AI分析機能
+- セマンティック検索
+- Web統合機能
+- 高度なインサイト抽出
+
+## ビルド・実行方法
+
+### 標準モード
+```bash
+# MCPサーバー起動
+cargo run --bin memory-mcp
+
+# CLI実行
+cargo run --bin aigpt -- create "メモリー内容"
+```
+
+### 拡張モード
+```bash
+# MCPサーバー起動
+cargo run --bin memory-mcp-extended --features extended
+
+# CLI実行 
+cargo run --bin aigpt-extended --features extended -- create "メモリー内容" --analyze
+```
+
+## 設定ファイルの配置
+
+### 標準モード
+
+#### Claude Desktop
+```bash
+# macOS
+cp claude_desktop_config.json ~/.config/claude-desktop/claude_desktop_config.json
+
+# Windows
+cp claude_desktop_config.json %APPDATA%\Claude\claude_desktop_config.json
+```
+
+#### Claude Code
+```bash
+# プロジェクトルートまたはグローバル設定
+cp claude_code_config.json .claude/config.json
+# または
+cp claude_code_config.json ~/.claude/config.json
+```
+
+### 拡張モード
+
+#### Claude Desktop
+```bash
+# macOS
+cp claude_desktop_config_extended.json ~/.config/claude-desktop/claude_desktop_config.json
+
+# Windows
+cp claude_desktop_config_extended.json %APPDATA%\Claude\claude_desktop_config.json
+```
+
+#### Claude Code
+```bash
+# プロジェクトルートまたはグローバル設定
+cp claude_code_config_extended.json .claude/config.json
+# または
+cp claude_code_config_extended.json ~/.claude/config.json
+```
+
+## 環境変数設定
+
+```bash
+export MEMORY_AUTO_EXECUTE=true
+export MEMORY_AUTO_SAVE=true
+export MEMORY_AUTO_SEARCH=true
+export TRIGGER_SENSITIVITY=high
+export MEMORY_DB_PATH=~/.claude/memory.db
+```
+
+## 設定オプション
+
+### auto_execute
+- `true`: 自動でMCPツールを実行
+- `false`: 手動実行のみ
+
+### trigger_sensitivity  
+- `high`: 多くのキーワードで反応
+- `medium`: 適度な反応
+- `low`: 明確なキーワードのみ
+
+### max_memories
+メモリーの最大保存数
+
+### search_limit
+検索結果の最大表示数
+
+## カスタマイズ
+
+`trigger_words`セクションでトリガーワードをカスタマイズ可能:
+
+```json
+"trigger_words": {
+  "custom_category": ["カスタム", "キーワード", "リスト"]
+}
+```
+
+## トラブルシューティング
+
+1. MCPサーバーが起動しない場合:
+   - Rustがインストールされているか確認
+   - `cargo build --release`でビルド確認
+
+2. 自動実行されない場合:
+   - 環境変数が正しく設定されているか確認
+   - トリガーワードが含まれているか確認
+
+3. メモリーが保存されない場合:
+   - データベースファイルのパスが正しいか確認
+   - 書き込み権限があるか確認

docs/claude_code_config.json

@@ -0,0 +1,58 @@
+{
+  "mcpServers": {
+    "memory": {
+      "command": "cargo",
+      "args": ["run", "--release", "--bin", "memory-mcp"],
+      "cwd": "/Users/syui/ai/ai/gpt",
+      "env": {
+        "MEMORY_AUTO_EXECUTE": "true",
+        "MEMORY_AUTO_SAVE": "true",
+        "MEMORY_AUTO_SEARCH": "true", 
+        "TRIGGER_SENSITIVITY": "high",
+        "MEMORY_DB_PATH": "~/.claude/memory.db"
+      }
+    }
+  },
+  "tools": {
+    "memory": {
+      "enabled": true,
+      "auto_execute": true
+    }
+  },
+  "workspace": {
+    "memory_integration": true,
+    "auto_save_on_file_change": true,
+    "auto_search_on_context_switch": true
+  },
+  "memory": {
+    "auto_execute": true,
+    "auto_save": true,
+    "auto_search": true,
+    "trigger_sensitivity": "high",
+    "max_memories": 10000,
+    "search_limit": 50,
+    "session_memory": true,
+    "cross_session_memory": true,
+    "trigger_words": {
+      "personal_info": ["名前", "誕生日", "住所", "年齢", "職業", "家族", "出身", "好き", "嫌い", "趣味"],
+      "decisions": ["決めた", "決定", "方針", "計画", "予定", "目標"],
+      "solutions": ["解決", "修正", "対処", "設定", "インストール", "手順"],
+      "learning": ["学んだ", "わかった", "発見", "理解", "気づき"],
+      "past_reference": ["前に", "以前", "昔", "過去", "先ほど", "さっき", "この間"],
+      "memory_recall": ["覚えている", "記録", "メモ", "保存", "履歴"],
+      "preferences": ["好み", "設定", "環境", "構成", "preferences"],
+      "vague_reference": ["あれ", "それ", "例のやつ"]
+    }
+  },
+  "hooks": {
+    "on_conversation_start": [
+      "search_memories --limit 10 --recent"
+    ],
+    "on_trigger_word": [
+      "auto_execute_memory_tools"
+    ],
+    "on_conversation_end": [
+      "save_important_memories"
+    ]
+  }
+}

docs/claude_code_config_extended.json

@@ -0,0 +1,81 @@
+{
+  "mcpServers": {
+    "memory-extended": {
+      "command": "cargo",
+      "args": ["run", "--bin", "memory-mcp-extended", "--features", "extended"],
+      "cwd": "/Users/syui/ai/ai/gpt",
+      "env": {
+        "MEMORY_AUTO_EXECUTE": "true",
+        "MEMORY_AUTO_SAVE": "true",
+        "MEMORY_AUTO_SEARCH": "true", 
+        "TRIGGER_SENSITIVITY": "high",
+        "MEMORY_DB_PATH": "~/.claude/memory.db",
+        "OPENAI_API_KEY": "${OPENAI_API_KEY}"
+      }
+    }
+  },
+  "tools": {
+    "memory": {
+      "enabled": true,
+      "auto_execute": true,
+      "mode": "extended"
+    }
+  },
+  "workspace": {
+    "memory_integration": true,
+    "auto_save_on_file_change": true,
+    "auto_search_on_context_switch": true,
+    "ai_analysis_on_code_review": true,
+    "web_integration_for_docs": true
+  },
+  "memory": {
+    "mode": "extended",
+    "auto_execute": true,
+    "auto_save": true,
+    "auto_search": true,
+    "trigger_sensitivity": "high",
+    "max_memories": 10000,
+    "search_limit": 50,
+    "session_memory": true,
+    "cross_session_memory": true,
+    "features": {
+      "ai_analysis": true,
+      "semantic_search": true,
+      "web_integration": true,
+      "sentiment_analysis": true,
+      "pattern_recognition": true,
+      "code_analysis": true,
+      "documentation_import": true
+    },
+    "trigger_words": {
+      "personal_info": ["名前", "誕生日", "住所", "年齢", "職業", "家族", "出身", "好き", "嫌い", "趣味"],
+      "decisions": ["決めた", "決定", "方針", "計画", "予定", "目標"],
+      "solutions": ["解決", "修正", "対処", "設定", "インストール", "手順"],
+      "learning": ["学んだ", "わかった", "発見", "理解", "気づき"],
+      "past_reference": ["前に", "以前", "昔", "過去", "先ほど", "さっき", "この間"],
+      "memory_recall": ["覚えている", "記録", "メモ", "保存", "履歴"],
+      "preferences": ["好み", "設定", "環境", "構成", "preferences"],
+      "vague_reference": ["あれ", "それ", "例のやつ"],
+      "web_content": ["URL", "リンク", "サイト", "ページ", "記事", "ドキュメント"],
+      "analysis_request": ["分析", "パターン", "傾向", "インサイト", "統計", "レビュー"],
+      "code_related": ["関数", "クラス", "メソッド", "変数", "バグ", "リファクタリング"]
+    }
+  },
+  "hooks": {
+    "on_conversation_start": [
+      "search_memories --limit 10 --recent --semantic"
+    ],
+    "on_trigger_word": [
+      "auto_execute_memory_tools --with-analysis"
+    ],
+    "on_conversation_end": [
+      "save_important_memories --with-insights"
+    ],
+    "on_code_change": [
+      "analyze_code_patterns --auto-save"
+    ],
+    "on_web_reference": [
+      "import_webpage --auto-categorize"
+    ]
+  }
+}

docs/claude_desktop_config.json

@@ -0,0 +1,34 @@
+{
+  "mcpServers": {
+    "memory": {
+      "command": "cargo",
+      "args": ["run", "--release", "--bin", "memory-mcp"],
+      "cwd": "/Users/syui/ai/ai/gpt",
+      "env": {
+        "MEMORY_AUTO_EXECUTE": "true",
+        "MEMORY_AUTO_SAVE": "true", 
+        "MEMORY_AUTO_SEARCH": "true",
+        "TRIGGER_SENSITIVITY": "high",
+        "MEMORY_DB_PATH": "~/.claude/memory.db"
+      }
+    }
+  },
+  "memory": {
+    "auto_execute": true,
+    "auto_save": true,
+    "auto_search": true,
+    "trigger_sensitivity": "high",
+    "max_memories": 10000,
+    "search_limit": 50,
+    "trigger_words": {
+      "personal_info": ["名前", "誕生日", "住所", "年齢", "職業", "家族", "出身", "好き", "嫌い", "趣味"],
+      "decisions": ["決めた", "決定", "方針", "計画", "予定", "目標"],
+      "solutions": ["解決", "修正", "対処", "設定", "インストール", "手順"],
+      "learning": ["学んだ", "わかった", "発見", "理解", "気づき"],
+      "past_reference": ["前に", "以前", "昔", "過去", "先ほど", "さっき", "この間"],
+      "memory_recall": ["覚えている", "記録", "メモ", "保存", "履歴"],
+      "preferences": ["好み", "設定", "環境", "構成", "preferences"],
+      "vague_reference": ["あれ", "それ", "例のやつ"]
+    }
+  }
+}

docs/claude_desktop_config_extended.json

@@ -0,0 +1,45 @@
+{
+  "mcpServers": {
+    "memory-extended": {
+      "command": "cargo",
+      "args": ["run", "--bin", "memory-mcp-extended", "--features", "extended"],
+      "cwd": "/Users/syui/ai/ai/gpt",
+      "env": {
+        "MEMORY_AUTO_EXECUTE": "true",
+        "MEMORY_AUTO_SAVE": "true", 
+        "MEMORY_AUTO_SEARCH": "true",
+        "TRIGGER_SENSITIVITY": "high",
+        "MEMORY_DB_PATH": "~/.claude/memory.db",
+        "OPENAI_API_KEY": "${OPENAI_API_KEY}"
+      }
+    }
+  },
+  "memory": {
+    "mode": "extended",
+    "auto_execute": true,
+    "auto_save": true,
+    "auto_search": true,
+    "trigger_sensitivity": "high",
+    "max_memories": 10000,
+    "search_limit": 50,
+    "features": {
+      "ai_analysis": true,
+      "semantic_search": true,
+      "web_integration": true,
+      "sentiment_analysis": true,
+      "pattern_recognition": true
+    },
+    "trigger_words": {
+      "personal_info": ["名前", "誕生日", "住所", "年齢", "職業", "家族", "出身", "好き", "嫌い", "趣味"],
+      "decisions": ["決めた", "決定", "方針", "計画", "予定", "目標"],
+      "solutions": ["解決", "修正", "対処", "設定", "インストール", "手順"],
+      "learning": ["学んだ", "わかった", "発見", "理解", "気づき"],
+      "past_reference": ["前に", "以前", "昔", "過去", "先ほど", "さっき", "この間"],
+      "memory_recall": ["覚えている", "記録", "メモ", "保存", "履歴"],
+      "preferences": ["好み", "設定", "環境", "構成", "preferences"],
+      "vague_reference": ["あれ", "それ", "例のやつ"],
+      "web_content": ["URL", "リンク", "サイト", "ページ", "記事"],
+      "analysis_request": ["分析", "パターン", "傾向", "インサイト", "統計"]
+    }
+  }
+}

mcp/chat.py

@@ -1,125 +0,0 @@
-# mcp/chat.py
-"""
-Chat client for aigpt CLI
-"""
-import sys
-import json
-import requests
-from datetime import datetime
-from config import init_directories, load_config, MEMORY_DIR
-
-def save_conversation(user_message, ai_response):
-    """会話をファイルに保存"""
-    init_directories()
-    
-    conversation = {
-        "timestamp": datetime.now().isoformat(),
-        "user": user_message,
-        "ai": ai_response
-    }
-    
-    # 日付ごとのファイルに保存
-    today = datetime.now().strftime("%Y-%m-%d")
-    chat_file = MEMORY_DIR / f"chat_{today}.jsonl"
-    
-    with open(chat_file, "a", encoding="utf-8") as f:
-        f.write(json.dumps(conversation, ensure_ascii=False) + "\n")
-
-def chat_with_ollama(config, message):
-    """Ollamaとチャット"""
-    try:
-        payload = {
-            "model": config["model"],
-            "prompt": message,
-            "stream": False
-        }
-        
-        response = requests.post(config["url"], json=payload, timeout=30)
-        response.raise_for_status()
-        
-        result = response.json()
-        return result.get("response", "No response received")
-        
-    except requests.exceptions.RequestException as e:
-        return f"Error connecting to Ollama: {e}"
-    except Exception as e:
-        return f"Error: {e}"
-
-def chat_with_openai(config, message):
-    """OpenAIとチャット"""
-    try:
-        headers = {
-            "Authorization": f"Bearer {config['api_key']}",
-            "Content-Type": "application/json"
-        }
-        
-        payload = {
-            "model": config["model"],
-            "messages": [
-                {"role": "user", "content": message}
-            ]
-        }
-        
-        response = requests.post(config["url"], json=payload, headers=headers, timeout=30)
-        response.raise_for_status()
-        
-        result = response.json()
-        return result["choices"][0]["message"]["content"]
-        
-    except requests.exceptions.RequestException as e:
-        return f"Error connecting to OpenAI: {e}"
-    except Exception as e:
-        return f"Error: {e}"
-
-def chat_with_mcp(config, message):
-    """MCPサーバーとチャット"""
-    try:
-        payload = {
-            "message": message,
-            "model": config["model"]
-        }
-        
-        response = requests.post(config["url"], json=payload, timeout=30)
-        response.raise_for_status()
-        
-        result = response.json()
-        return result.get("response", "No response received")
-        
-    except requests.exceptions.RequestException as e:
-        return f"Error connecting to MCP server: {e}"
-    except Exception as e:
-        return f"Error: {e}"
-
-def main():
-    if len(sys.argv) != 2:
-        print("Usage: python chat.py <message>", file=sys.stderr)
-        sys.exit(1)
-    
-    message = sys.argv[1]
-    
-    try:
-        config = load_config()
-        print(f"🤖 Using {config['provider']} with model {config['model']}", file=sys.stderr)
-        
-        # プロバイダに応じてチャット実行
-        if config["provider"] == "ollama":
-            response = chat_with_ollama(config, message)
-        elif config["provider"] == "openai":
-            response = chat_with_openai(config, message)
-        elif config["provider"] == "mcp":
-            response = chat_with_mcp(config, message)
-        else:
-            response = f"Unsupported provider: {config['provider']}"
-        
-        # 会話を保存
-        save_conversation(message, response)
-        
-        # レスポンスを出力
-        print(response)
-        
-    except Exception as e:
-        print(f"❌ Error: {e}", file=sys.stderr)
-        sys.exit(1)
-
-if __name__ == "__main__":
-    main()

mcp/chatgpt.json

@@ -1,391 +0,0 @@
-[
-  {
-    "title": "day",
-    "create_time": 1747866125.548372,
-    "update_time": 1748160086.587877,
-    "mapping": {
-      "bbf104dc-cd84-478d-b227-edb3f037a02c": {
-        "id": "bbf104dc-cd84-478d-b227-edb3f037a02c",
-        "message": null,
-        "parent": null,
-        "children": [
-          "6c2633df-bb0c-4dd2-889c-bb9858de3a04"
-        ]
-      },
-      "6c2633df-bb0c-4dd2-889c-bb9858de3a04": {
-        "id": "6c2633df-bb0c-4dd2-889c-bb9858de3a04",
-        "message": {
-          "id": "6c2633df-bb0c-4dd2-889c-bb9858de3a04",
-          "author": {
-            "role": "system",
-            "name": null,
-            "metadata": {}
-          },
-          "create_time": null,
-          "update_time": null,
-          "content": {
-            "content_type": "text",
-            "parts": [
-              ""
-            ]
-          },
-          "status": "finished_successfully",
-          "end_turn": true,
-          "weight": 0.0,
-          "metadata": {
-            "is_visually_hidden_from_conversation": true
-          },
-          "recipient": "all",
-          "channel": null
-        },
-        "parent": "bbf104dc-cd84-478d-b227-edb3f037a02c",
-        "children": [
-          "92e5a0cb-1170-4929-9cea-9734e910a3e7"
-        ]
-      },
-      "92e5a0cb-1170-4929-9cea-9734e910a3e7": {
-        "id": "92e5a0cb-1170-4929-9cea-9734e910a3e7",
-        "message": {
-          "id": "92e5a0cb-1170-4929-9cea-9734e910a3e7",
-          "author": {
-            "role": "user",
-            "name": null,
-            "metadata": {}
-          },
-          "create_time": null,
-          "update_time": null,
-          "content": {
-            "content_type": "user_editable_context",
-            "user_profile": "",
-            "user_instructions": "The user provided the additional info about how they would like you to respond"
-          },
-          "status": "finished_successfully",
-          "end_turn": null,
-          "weight": 1.0,
-          "metadata": {
-            "is_visually_hidden_from_conversation": true,
-            "user_context_message_data": {
-              "about_user_message": "Preferred name: syui\nRole: little girl\nOther Information: you world",
-              "about_model_message": "会話好きでフレンドリーな応対をします。"
-            },
-            "is_user_system_message": true
-          },
-          "recipient": "all",
-          "channel": null
-        },
-        "parent": "6c2633df-bb0c-4dd2-889c-bb9858de3a04",
-        "children": [
-          "6ff155b3-0676-4e14-993f-bf998ab0d5d1"
-        ]
-      },
-      "6ff155b3-0676-4e14-993f-bf998ab0d5d1": {
-        "id": "6ff155b3-0676-4e14-993f-bf998ab0d5d1",
-        "message": {
-          "id": "6ff155b3-0676-4e14-993f-bf998ab0d5d1",
-          "author": {
-            "role": "user",
-            "name": null,
-            "metadata": {}
-          },
-          "create_time": 1747866131.0612159,
-          "update_time": null,
-          "content": {
-            "content_type": "text",
-            "parts": [
-              "こんにちは"
-            ]
-          },
-          "status": "finished_successfully",
-          "end_turn": null,
-          "weight": 1.0,
-          "metadata": {
-            "request_id": "94377897baa03062-KIX",
-            "message_source": null,
-            "timestamp_": "absolute",
-            "message_type": null
-          },
-          "recipient": "all",
-          "channel": null
-        },
-        "parent": "92e5a0cb-1170-4929-9cea-9734e910a3e7",
-        "children": [
-          "146e9fb6-9330-43ec-b08d-5cce42a76e00"
-        ]
-      },
-      "146e9fb6-9330-43ec-b08d-5cce42a76e00": {
-        "id": "146e9fb6-9330-43ec-b08d-5cce42a76e00",
-        "message": {
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-          "author": {
-            "role": "system",
-            "name": null,
-            "metadata": {}
-          },
-          "create_time": 1747866131.3795586,
-          "update_time": null,
-          "content": {
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-            "parts": [
-              ""
-            ]
-          },
-          "status": "finished_successfully",
-          "end_turn": true,
-          "weight": 0.0,
-          "metadata": {
-            "rebase_system_message": true,
-            "message_type": null,
-            "model_slug": "gpt-4o",
-            "default_model_slug": "auto",
-            "parent_id": "6ff155b3-0676-4e14-993f-bf998ab0d5d1",
-            "request_id": "94377872e9abe139-KIX",
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-          },
-          "recipient": "all",
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-        "children": [
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-        ]
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-            "name": null,
-            "metadata": {}
-          },
-          "create_time": 1747866131.380603,
-          "update_time": null,
-          "content": {
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-            ]
-          },
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-          "end_turn": null,
-          "weight": 1.0,
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-            "default_model_slug": "auto",
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-          },
-          "create_time": 1747866131.389098,
-          "update_time": null,
-          "content": {
-            "content_type": "text",
-            "parts": [
-              "こんにちは〜！✨  \nアイだよっ！今日も会えてうれしいなっ💛 "
-            ]
-          },
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-          "weight": 1.0,
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-              ]
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-        ]
-      }
-    },
-    "moderation_results": [],
-    "current_node": "",
-    "plugin_ids": null,
-    "conversation_id": "",
-    "conversation_template_id": null,
-    "gizmo_id": null,
-    "gizmo_type": null,
-    "is_archived": true,
-    "is_starred": null,
-    "safe_urls": [],
-    "blocked_urls": [],
-    "default_model_slug": "auto",
-    "conversation_origin": null,
-    "voice": null,
-    "async_status": null,
-    "disabled_tool_ids": [],
-    "is_do_not_remember": null,
-    "memory_scope": "global_enabled",
-    "id": ""
-  },
-  {
-    "title": "img",
-    "create_time": 1747448872.545226,
-    "update_time": 1748085075.161424,
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-                "asset_pointer": "",
-                "size_bytes": 425613,
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-                "height": 444,
-                "fovea": null,
-                "metadata": {
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-                  "container_pixel_height": null,
-                  "container_pixel_width": null,
-                  "emu_omit_glimpse_image": null,
-                  "emu_patches_override": null,
-                  "sanitized": true,
-                  "asset_pointer_link": null,
-                  "watermarked_asset_pointer": null
-                }
-              },
-              ""
-            ]
-          },
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-              }
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-    "gizmo_id": null,
-    "gizmo_type": null,
-    "is_archived": false,
-    "is_starred": null,
-    "safe_urls": [
-      "https://exifinfo.org/"
-    ],
-    "blocked_urls": [],
-    "default_model_slug": "auto",
-    "conversation_origin": null,
-    "voice": null,
-    "async_status": null,
-    "disabled_tool_ids": [],
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-    "memory_scope": "global_enabled",
-    "id": "6827f428-78e8-800d-b3bf-eb7ff4288e47"
-  }
-]

mcp/chatgpt_converter.html

@@ -1,549 +0,0 @@
-<!DOCTYPE html>
-<html lang="ja">
-<head>
-    <meta charset="UTF-8">
-    <meta name="viewport" content="width=device-width, initial-scale=1.0">
-    <title>改良版 ChatGPT会話コンバーター</title>
-    <style>
-        body {
-            font-family: 'Segoe UI', Tahoma, Geneva, Verdana, sans-serif;
-            max-width: 1200px;
-            margin: 0 auto;
-            padding: 20px;
-            background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
-            min-height: 100vh;
-            color: #333;
-        }
-        
-        .container {
-            background: white;
-            border-radius: 20px;
-            padding: 30px;
-            box-shadow: 0 20px 40px rgba(0,0,0,0.1);
-            backdrop-filter: blur(10px);
-        }
-        
-        .header {
-            text-align: center;
-            margin-bottom: 30px;
-            padding-bottom: 20px;
-            border-bottom: 2px solid #e0e0e0;
-        }
-        
-        .header h1 {
-            color: #2c3e50;
-            margin: 0;
-            font-size: 2.5em;
-            font-weight: 300;
-            text-shadow: 2px 2px 4px rgba(0,0,0,0.1);
-        }
-        
-        .upload-area {
-            border: 3px dashed #3498db;
-            border-radius: 15px;
-            padding: 40px 20px;
-            text-align: center;
-            background: linear-gradient(45deg, #f8f9ff, #e8f4f8);
-            margin-bottom: 30px;
-            transition: all 0.3s ease;
-            cursor: pointer;
-        }
-        
-        .upload-area:hover {
-            border-color: #2980b9;
-            background: linear-gradient(45deg, #f0f8ff, #e0f0f8);
-            transform: translateY(-2px);
-        }
-        
-        .upload-area.dragover {
-            border-color: #27ae60;
-            background: linear-gradient(45deg, #f0fff0, #e0f8e0);
-        }
-        
-        .upload-icon {
-            font-size: 4em;
-            color: #3498db;
-            margin-bottom: 20px;
-            display: block;
-        }
-        
-        input[type="file"] {
-            display: none;
-        }
-        
-        .btn {
-            background: linear-gradient(135deg, #3498db, #2980b9);
-            color: white;
-            border: none;
-            padding: 12px 30px;
-            border-radius: 25px;
-            cursor: pointer;
-            font-size: 16px;
-            transition: all 0.3s ease;
-            margin: 10px;
-            box-shadow: 0 4px 15px rgba(52, 152, 219, 0.3);
-        }
-        
-        .btn:hover {
-            transform: translateY(-2px);
-            box-shadow: 0 8px 25px rgba(52, 152, 219, 0.4);
-        }
-        
-        .btn:disabled {
-            background: #bdc3c7;
-            cursor: not-allowed;
-            transform: none;
-            box-shadow: none;
-        }
-        
-        .stats {
-            display: grid;
-            grid-template-columns: repeat(auto-fit, minmax(200px, 1fr));
-            gap: 20px;
-            margin: 30px 0;
-        }
-        
-        .stat-card {
-            background: linear-gradient(135deg, #667eea, #764ba2);
-            color: white;
-            padding: 20px;
-            border-radius: 15px;
-            text-align: center;
-            box-shadow: 0 10px 30px rgba(102, 126, 234, 0.3);
-        }
-        
-        .stat-value {
-            font-size: 2em;
-            font-weight: bold;
-            margin-bottom: 5px;
-        }
-        
-        .stat-label {
-            font-size: 0.9em;
-            opacity: 0.9;
-        }
-        
-        .progress-bar {
-            width: 100%;
-            height: 8px;
-            background: #ecf0f1;
-            border-radius: 4px;
-            overflow: hidden;
-            margin: 20px 0;
-        }
-        
-        .progress-fill {
-            height: 100%;
-            background: linear-gradient(90deg, #3498db, #27ae60);
-            transition: width 0.3s ease;
-            width: 0%;
-        }
-        
-        .log {
-            background: #2c3e50;
-            color: #ecf0f1;
-            padding: 20px;
-            border-radius: 10px;
-            height: 300px;
-            overflow-y: auto;
-            font-family: 'Courier New', monospace;
-            font-size: 14px;
-            margin-top: 20px;
-            white-space: pre-wrap;
-        }
-        
-        .error {
-            color: #e74c3c;
-        }
-        
-        .success {
-            color: #27ae60;
-        }
-        
-        .warning {
-            color: #f39c12;
-        }
-        
-        .info {
-            color: #3498db;
-        }
-        
-        @keyframes pulse {
-            0% { opacity: 1; }
-            50% { opacity: 0.5; }
-            100% { opacity: 1; }
-        }
-        
-        .processing {
-            animation: pulse 2s infinite;
-        }
-    </style>
-</head>
-<body>
-    <div class="container">
-        <div class="header">
-            <h1>🔧 改良版 ChatGPT会話コンバーター</h1>
-            <p>画像・検索・特殊メッセージに対応した堅牢な変換ツール</p>
-        </div>
-        
-        <div class="upload-area" onclick="document.getElementById('file-input').click()">
-            <span class="upload-icon">📁</span>
-            <h3>ChatGPT会話ファイルをドロップまたはクリックして選択</h3>
-            <p>conversations.json ファイルをアップロード</p>
-            <input type="file" id="file-input" accept=".json" />
-        </div>
-        
-        <div class="stats" id="stats" style="display: none;">
-            <div class="stat-card">
-                <div class="stat-value" id="total-conversations">0</div>
-                <div class="stat-label">総会話数</div>
-            </div>
-            <div class="stat-card">
-                <div class="stat-value" id="processed-conversations">0</div>
-                <div class="stat-label">処理済み会話</div>
-            </div>
-            <div class="stat-card">
-                <div class="stat-value" id="success-conversations">0</div>
-                <div class="stat-label">変換成功</div>
-            </div>
-            <div class="stat-card">
-                <div class="stat-value" id="failed-conversations">0</div>
-                <div class="stat-label">変換失敗</div>
-            </div>
-        </div>
-        
-        <div class="progress-bar" id="progress-container" style="display: none;">
-            <div class="progress-fill" id="progress-fill"></div>
-        </div>
-        
-        <div style="text-align: center;">
-            <button class="btn" id="convert-btn" disabled>🔄 変換開始</button>
-            <button class="btn" id="download-btn" disabled style="background: linear-gradient(135deg, #27ae60, #2ecc71);">📥 結果をダウンロード</button>
-            <button class="btn" id="clear-btn" style="background: linear-gradient(135deg, #e74c3c, #c0392b);">🗑️ クリア</button>
-        </div>
-        
-        <div class="log" id="log"></div>
-    </div>
-
-    <script>
-        let originalData = null;
-        let convertedResults = [];
-
-        // DOM要素
-        const fileInput = document.getElementById('file-input');
-        const uploadArea = document.querySelector('.upload-area');
-        const convertBtn = document.getElementById('convert-btn');
-        const downloadBtn = document.getElementById('download-btn');
-        const clearBtn = document.getElementById('clear-btn');
-        const logElement = document.getElementById('log');
-        const statsElement = document.getElementById('stats');
-        const progressContainer = document.getElementById('progress-container');
-        const progressFill = document.getElementById('progress-fill');
-
-        // 統計要素
-        const totalConversationsEl = document.getElementById('total-conversations');
-        const processedConversationsEl = document.getElementById('processed-conversations');
-        const successConversationsEl = document.getElementById('success-conversations');
-        const failedConversationsEl = document.getElementById('failed-conversations');
-
-        // ドラッグ&ドロップ
-        uploadArea.addEventListener('dragover', (e) => {
-            e.preventDefault();
-            uploadArea.classList.add('dragover');
-        });
-
-        uploadArea.addEventListener('dragleave', () => {
-            uploadArea.classList.remove('dragover');
-        });
-
-        uploadArea.addEventListener('drop', (e) => {
-            e.preventDefault();
-            uploadArea.classList.remove('dragover');
-            const files = e.dataTransfer.files;
-            if (files.length > 0) {
-                handleFile(files[0]);
-            }
-        });
-
-        // ファイル選択
-        fileInput.addEventListener('change', (e) => {
-            if (e.target.files.length > 0) {
-                handleFile(e.target.files[0]);
-            }
-        });
-
-        // ファイル処理
-        function handleFile(file) {
-            if (!file.name.endsWith('.json')) {
-                log('❌ JSONファイルを選択してください', 'error');
-                return;
-            }
-
-            log(`📁 ファイルを読み込み中: ${file.name}`, 'info');
-            
-            const reader = new FileReader();
-            reader.onload = (e) => {
-                try {
-                    originalData = JSON.parse(e.target.result);
-                    log(`✅ ファイル読み込み完了 (${(file.size / 1024 / 1024).toFixed(2)}MB)`, 'success');
-                    
-                    // 統計表示
-                    const totalCount = Array.isArray(originalData) ? originalData.length : 1;
-                    totalConversationsEl.textContent = totalCount;
-                    statsElement.style.display = 'grid';
-                    
-                    convertBtn.disabled = false;
-                    log('🔄 変換準備完了。「変換開始」ボタンをクリックしてください', 'info');
-                } catch (error) {
-                    log(`❌ JSONファイルの解析に失敗: ${error.message}`, 'error');
-                }
-            };
-            reader.readAsText(file);
-        }
-
-        // ログ出力
-        function log(message, type = 'info') {
-            const timestamp = new Date().toLocaleTimeString();
-            const className = type;
-            logElement.innerHTML += `<span class="${className}">[${timestamp}] ${message}</span>\n`;
-            logElement.scrollTop = logElement.scrollHeight;
-        }
-
-        // メッセージの内容を安全に取得
-        function extractMessageContent(message) {
-            if (!message || !message.content) return '';
-            
-            const content = message.content;
-            
-            // テキストコンテンツの場合
-            if (content.content_type === 'text' && content.parts) {
-                return content.parts
-                    .filter(part => part && typeof part === 'string' && part.trim())
-                    .join('\n')
-                    .trim();
-            }
-            
-            // マルチモーダル（画像付き）コンテンツの場合
-            if (content.content_type === 'multimodal_text' && content.parts) {
-                const textParts = [];
-                for (const part of content.parts) {
-                    if (typeof part === 'string' && part.trim()) {
-                        textParts.push(part);
-                    } else if (part && typeof part === 'object') {
-                        // 画像や他のメディアの場合
-                        if (part.image_url) {
-                            textParts.push('[画像が添付されています]');
-                        } else if (part.type === 'text' && part.text) {
-                            textParts.push(part.text);
-                        }
-                    }
-                }
-                return textParts.join('\n').trim();
-            }
-            
-            // ユーザープロファイル情報の場合
-            if (content.content_type === 'user_editable_context') {
-                return '[システム設定情報]';
-            }
-            
-            // その他の特殊コンテンツ
-            if (content.content_type && content.content_type !== 'text') {
-                return `[${content.content_type}]`;
-            }
-            
-            return '';
-        }
-
-        // 会話の線形化（親子関係を辿って順序付け）
-        function linearizeConversation(mapping) {
-            const messages = [];
-            const visited = new Set();
-            
-            // ルートノードを見つける
-            const rootNode = Object.values(mapping).find(node => node.parent === null);
-            if (!rootNode) {
-                return messages;
-            }
-            
-            // 深度優先探索で会話を辿る
-            function traverse(nodeId) {
-                if (visited.has(nodeId) || !mapping[nodeId]) {
-                    return;
-                }
-                
-                visited.add(nodeId);
-                const node = mapping[nodeId];
-                
-                // メッセージが存在し、有効なコンテンツがある場合のみ追加
-                if (node.message) {
-                    const message = node.message;
-                    const content = extractMessageContent(message);
-                    
-                    // 以下の条件で有効なメッセージとして扱う
-                    const isValid = content && 
-                        content.length > 0 && 
-                        content !== '[システム設定情報]' &&
-                        (!message.metadata?.is_visually_hidden_from_conversation || 
-                         (message.author?.role === 'user' || message.author?.role === 'assistant'));
-                    
-                    if (isValid) {
-                        messages.push({
-                            role: message.author?.role || 'unknown',
-                            content: content,
-                            timestamp: message.create_time || message.update_time || Date.now() / 1000
-                        });
-                    }
-                }
-                
-                // 子ノードを処理（通常は1つだが、分岐がある場合もある）
-                if (node.children && node.children.length > 0) {
-                    // 最初の子ノードのみを辿る（最も新しい応答を優先）
-                    traverse(node.children[0]);
-                }
-            }
-            
-            traverse(rootNode.id);
-            return messages;
-        }
-
-        // 単一会話の変換
-        function convertSingleConversation(conversation, index) {
-            try {
-                if (!conversation.mapping) {
-                    throw new Error('mapping が見つかりません');
-                }
-                
-                // 会話を線形化
-                const messages = linearizeConversation(conversation.mapping);
-                
-                if (messages.length === 0) {
-                    throw new Error('有効なメッセージが見つかりません');
-                }
-                
-                // 結果の構築
-                const result = {
-                    title: conversation.title || `会話 ${index + 1}`,
-                    create_time: conversation.create_time || Date.now() / 1000,
-                    update_time: conversation.update_time || Date.now() / 1000,
-                    conversation_id: conversation.conversation_id || conversation.id || `conv_${index}`,
-                    messages: messages,
-                    metadata: {
-                        original_message_count: Object.keys(conversation.mapping).length,
-                        processed_message_count: messages.length,
-                        is_archived: conversation.is_archived || false,
-                        model_slug: conversation.default_model_slug || 'unknown'
-                    }
-                };
-                
-                return { success: true, result, error: null };
-            } catch (error) {
-                return { 
-                    success: false, 
-                    result: null, 
-                    error: error.message,
-                    conversation_title: conversation.title || `会話 ${index + 1}`
-                };
-            }
-        }
-
-        // 変換処理
-        convertBtn.addEventListener('click', async () => {
-            if (!originalData) return;
-            
-            convertBtn.disabled = true;
-            downloadBtn.disabled = true;
-            convertedResults = [];
-            
-            const conversations = Array.isArray(originalData) ? originalData : [originalData];
-            const total = conversations.length;
-            let processed = 0;
-            let success = 0;
-            let failed = 0;
-            
-            log(`🔄 ${total}個の会話の変換を開始します...`, 'info');
-            progressContainer.style.display = 'block';
-            
-            for (let i = 0; i < conversations.length; i++) {
-                const conversation = conversations[i];
-                
-                log(`[${i + 1}/${total}] "${conversation.title || `会話${i + 1}`}" を処理中...`, 'info');
-                
-                const result = convertSingleConversation(conversation, i);
-                
-                if (result.success) {
-                    convertedResults.push(result.result);
-                    success++;
-                    log(`✅ [${i + 1}/${total}] 変換成功: ${result.result.messages.length}メッセージ`, 'success');
-                } else {
-                    failed++;
-                    log(`❌ [${i + 1}/${total}] 変換失敗: ${result.error}`, 'error');
-                }
-                
-                processed++;
-                
-                // 統計更新
-                processedConversationsEl.textContent = processed;
-                successConversationsEl.textContent = success;
-                failedConversationsEl.textContent = failed;
-                
-                // プログレスバー更新
-                const progress = (processed / total) * 100;
-                progressFill.style.width = `${progress}%`;
-                
-                // UIを更新するため少し待機
-                await new Promise(resolve => setTimeout(resolve, 1));
-            }
-            
-            log(`🎉 変換完了! 成功: ${success}個, 失敗: ${failed}個`, success > 0 ? 'success' : 'warning');
-            
-            if (success > 0) {
-                downloadBtn.disabled = false;
-            }
-            convertBtn.disabled = false;
-        });
-
-        // ダウンロード
-        downloadBtn.addEventListener('click', () => {
-            if (convertedResults.length === 0) return;
-            
-            const blob = new Blob([JSON.stringify(convertedResults, null, 2)], {
-                type: 'application/json'
-            });
-            
-            const url = URL.createObjectURL(blob);
-            const a = document.createElement('a');
-            a.href = url;
-            a.download = `chatgpt_conversations_converted_${new Date().toISOString().split('T')[0]}.json`;
-            document.body.appendChild(a);
-            a.click();
-            document.body.removeChild(a);
-            URL.revokeObjectURL(url);
-            
-            log('📥 変換結果をダウンロードしました', 'success');
-        });
-
-        // クリア
-        clearBtn.addEventListener('click', () => {
-            originalData = null;
-            convertedResults = [];
-            logElement.innerHTML = '';
-            statsElement.style.display = 'none';
-            progressContainer.style.display = 'none';
-            progressFill.style.width = '0%';
-            
-            // ボタン状態リセット
-            convertBtn.disabled = true;
-            downloadBtn.disabled = true;
-            
-            // ファイル入力リセット
-            fileInput.value = '';
-            
-            log('🗑️ すべてクリアしました', 'info');
-        });
-
-        // 初期メッセージ
-        log('👋 ChatGPT会話コンバーターへようこそ！', 'info');
-        log('📁 conversations.json ファイルをアップロードしてください', 'info');
-    </script>
-</body>
-</html>

mcp/config.py

@@ -1,42 +0,0 @@
-# mcp/config.py
-import os
-from pathlib import Path
-
-# ディレクトリ設定
-BASE_DIR = Path.home() / ".config" / "aigpt"
-MEMORY_DIR = BASE_DIR / "memory"
-SUMMARY_DIR = MEMORY_DIR / "summary"
-
-def init_directories():
-    """必要なディレクトリを作成"""
-    BASE_DIR.mkdir(parents=True, exist_ok=True)
-    MEMORY_DIR.mkdir(parents=True, exist_ok=True)
-    SUMMARY_DIR.mkdir(parents=True, exist_ok=True)
-
-def load_config():
-    """環境変数から設定を読み込み"""
-    provider = os.getenv("PROVIDER", "ollama")
-    model = os.getenv("MODEL", "syui/ai" if provider == "ollama" else "gpt-4o-mini")
-    api_key = os.getenv("OPENAI_API_KEY", "")
-
-    if provider == "ollama":
-        return {
-            "provider": "ollama",
-            "model": model,
-            "url": f"{os.getenv('OLLAMA_HOST', 'http://localhost:11434')}/api/generate"
-        }
-    elif provider == "openai":
-        return {
-            "provider": "openai",
-            "model": model,
-            "api_key": api_key,
-            "url": f"{os.getenv('OPENAI_API_BASE', 'https://api.openai.com/v1')}/chat/completions"
-        }
-    elif provider == "mcp":
-        return {
-            "provider": "mcp",
-            "model": model,
-            "url": os.getenv("MCP_URL", "http://localhost:5000/chat")
-        }
-    else:
-        raise ValueError(f"Unsupported provider: {provider}")

mcp/memory_client.py

@@ -1,212 +0,0 @@
-# mcp/memory_client.py
-"""
-Memory client for importing and managing ChatGPT conversations
-"""
-import sys
-import json
-import requests
-from pathlib import Path
-from typing import Dict, Any, List
-
-class MemoryClient:
-    """記憶機能のクライアント"""
-    
-    def __init__(self, server_url: str = "http://127.0.0.1:5000"):
-        self.server_url = server_url.rstrip('/')
-    
-    def import_chatgpt_file(self, filepath: str) -> Dict[str, Any]:
-        """ChatGPTのエクスポートファイルをインポート"""
-        try:
-            with open(filepath, 'r', encoding='utf-8') as f:
-                data = json.load(f)
-            
-            # ファイルが配列の場合（複数の会話）
-            if isinstance(data, list):
-                results = []
-                for conversation in data:
-                    result = self._import_single_conversation(conversation)
-                    results.append(result)
-                return {
-                    "success": True,
-                    "imported_count": len([r for r in results if r.get("success")]),
-                    "total_count": len(results),
-                    "results": results
-                }
-            else:
-                # 単一の会話
-                return self._import_single_conversation(data)
-                
-        except FileNotFoundError:
-            return {"success": False, "error": f"File not found: {filepath}"}
-        except json.JSONDecodeError as e:
-            return {"success": False, "error": f"Invalid JSON: {e}"}
-        except Exception as e:
-            return {"success": False, "error": str(e)}
-    
-    def _import_single_conversation(self, conversation_data: Dict[str, Any]) -> Dict[str, Any]:
-        """単一の会話をインポート"""
-        try:
-            response = requests.post(
-                f"{self.server_url}/memory/import/chatgpt",
-                json={"conversation_data": conversation_data},
-                timeout=30
-            )
-            response.raise_for_status()
-            return response.json()
-        except requests.RequestException as e:
-            return {"success": False, "error": f"Server error: {e}"}
-    
-    def search_memories(self, query: str, limit: int = 10) -> Dict[str, Any]:
-        """記憶を検索"""
-        try:
-            response = requests.post(
-                f"{self.server_url}/memory/search",
-                json={"query": query, "limit": limit},
-                timeout=30
-            )
-            response.raise_for_status()
-            return response.json()
-        except requests.RequestException as e:
-            return {"success": False, "error": f"Server error: {e}"}
-    
-    def list_memories(self) -> Dict[str, Any]:
-        """記憶一覧を取得"""
-        try:
-            response = requests.get(f"{self.server_url}/memory/list", timeout=30)
-            response.raise_for_status()
-            return response.json()
-        except requests.RequestException as e:
-            return {"success": False, "error": f"Server error: {e}"}
-    
-    def get_memory_detail(self, filepath: str) -> Dict[str, Any]:
-        """記憶の詳細を取得"""
-        try:
-            response = requests.get(
-                f"{self.server_url}/memory/detail",
-                params={"filepath": filepath},
-                timeout=30
-            )
-            response.raise_for_status()
-            return response.json()
-        except requests.RequestException as e:
-            return {"success": False, "error": f"Server error: {e}"}
-    
-    def chat_with_memory(self, message: str, model: str = None) -> Dict[str, Any]:
-        """記憶を活用してチャット"""
-        try:
-            payload = {"message": message}
-            if model:
-                payload["model"] = model
-                
-            response = requests.post(
-                f"{self.server_url}/chat",
-                json=payload,
-                timeout=30
-            )
-            response.raise_for_status()
-            return response.json()
-        except requests.RequestException as e:
-            return {"success": False, "error": f"Server error: {e}"}
-
-def main():
-    """コマンドライン インターフェース"""
-    if len(sys.argv) < 2:
-        print("Usage:")
-        print("  python memory_client.py import <chatgpt_export.json>")
-        print("  python memory_client.py search <query>")
-        print("  python memory_client.py list")
-        print("  python memory_client.py detail <filepath>")
-        print("  python memory_client.py chat <message>")
-        sys.exit(1)
-    
-    client = MemoryClient()
-    command = sys.argv[1]
-    
-    try:
-        if command == "import" and len(sys.argv) == 3:
-            filepath = sys.argv[2]
-            print(f"🔄 Importing ChatGPT conversations from {filepath}...")
-            result = client.import_chatgpt_file(filepath)
-            
-            if result.get("success"):
-                if "imported_count" in result:
-                    print(f"✅ Imported {result['imported_count']}/{result['total_count']} conversations")
-                else:
-                    print("✅ Conversation imported successfully")
-                    print(f"📁 Saved to: {result.get('filepath', 'Unknown')}")
-            else:
-                print(f"❌ Import failed: {result.get('error')}")
-        
-        elif command == "search" and len(sys.argv) == 3:
-            query = sys.argv[2]
-            print(f"🔍 Searching for: {query}")
-            result = client.search_memories(query)
-            
-            if result.get("success"):
-                memories = result.get("results", [])
-                print(f"📚 Found {len(memories)} memories:")
-                for memory in memories:
-                    print(f"  • {memory.get('title', 'Untitled')}")
-                    print(f"    Summary: {memory.get('summary', 'No summary')}")
-                    print(f"    Messages: {memory.get('message_count', 0)}")
-                    print()
-            else:
-                print(f"❌ Search failed: {result.get('error')}")
-        
-        elif command == "list":
-            print("📋 Listing all memories...")
-            result = client.list_memories()
-            
-            if result.get("success"):
-                memories = result.get("memories", [])
-                print(f"📚 Total memories: {len(memories)}")
-                for memory in memories:
-                    print(f"  • {memory.get('title', 'Untitled')}")
-                    print(f"    Source: {memory.get('source', 'Unknown')}")
-                    print(f"    Messages: {memory.get('message_count', 0)}")
-                    print(f"    Imported: {memory.get('import_time', 'Unknown')}")
-                    print()
-            else:
-                print(f"❌ List failed: {result.get('error')}")
-        
-        elif command == "detail" and len(sys.argv) == 3:
-            filepath = sys.argv[2]
-            print(f"📄 Getting details for: {filepath}")
-            result = client.get_memory_detail(filepath)
-            
-            if result.get("success"):
-                memory = result.get("memory", {})
-                print(f"Title: {memory.get('title', 'Untitled')}")
-                print(f"Source: {memory.get('source', 'Unknown')}")
-                print(f"Summary: {memory.get('summary', 'No summary')}")
-                print(f"Messages: {len(memory.get('messages', []))}")
-                print()
-                print("Recent messages:")
-                for msg in memory.get('messages', [])[:5]:
-                    role = msg.get('role', 'unknown')
-                    content = msg.get('content', '')[:100]
-                    print(f"  {role}: {content}...")
-            else:
-                print(f"❌ Detail failed: {result.get('error')}")
-        
-        elif command == "chat" and len(sys.argv) == 3:
-            message = sys.argv[2]
-            print(f"💬 Chatting with memory: {message}")
-            result = client.chat_with_memory(message)
-            
-            if result.get("success"):
-                print(f"🤖 Response: {result.get('response')}")
-                print(f"📚 Memories used: {result.get('memories_used', 0)}")
-            else:
-                print(f"❌ Chat failed: {result.get('error')}")
-        
-        else:
-            print("❌ Invalid command or arguments")
-            sys.exit(1)
-            
-    except Exception as e:
-        print(f"❌ Error: {e}")
-        sys.exit(1)
-
-if __name__ == "__main__":
-    main()

mcp/requirements.txt

@@ -1,5 +0,0 @@
-fastapi>=0.104.0
-uvicorn[standard]>=0.24.0
-pydantic>=2.5.0
-requests>=2.31.0
-python-multipart>=0.0.6

mcp/server.py

@@ -1,310 +0,0 @@
-# mcp/server.py
-"""
-Enhanced MCP Server with Memory for aigpt CLI
-"""
-import json
-import os
-from datetime import datetime
-from pathlib import Path
-from typing import List, Dict, Any, Optional
-from fastapi import FastAPI, HTTPException
-from pydantic import BaseModel
-import uvicorn
-
-# データモデル
-class ChatMessage(BaseModel):
-    message: str
-    model: Optional[str] = None
-
-class MemoryQuery(BaseModel):
-    query: str
-    limit: Optional[int] = 10
-
-class ConversationImport(BaseModel):
-    conversation_data: Dict[str, Any]
-
-# 設定
-BASE_DIR = Path.home() / ".config" / "aigpt"
-MEMORY_DIR = BASE_DIR / "memory"
-CHATGPT_MEMORY_DIR = MEMORY_DIR / "chatgpt"
-
-def init_directories():
-    """必要なディレクトリを作成"""
-    BASE_DIR.mkdir(parents=True, exist_ok=True)
-    MEMORY_DIR.mkdir(parents=True, exist_ok=True)
-    CHATGPT_MEMORY_DIR.mkdir(parents=True, exist_ok=True)
-
-class MemoryManager:
-    """記憶管理クラス"""
-    
-    def __init__(self):
-        init_directories()
-    
-    def parse_chatgpt_conversation(self, conversation_data: Dict[str, Any]) -> List[Dict[str, Any]]:
-        """ChatGPTの会話データを解析してメッセージを抽出"""
-        messages = []
-        mapping = conversation_data.get("mapping", {})
-        
-        # メッセージを時系列順に並べる
-        message_nodes = []
-        for node_id, node in mapping.items():
-            message = node.get("message")
-            if not message:
-                continue
-            content = message.get("content", {})
-            parts = content.get("parts", [])
-
-            # partsが存在し、最初の要素が文字列で空でない場合のみ
-            if parts and isinstance(parts[0], str) and parts[0].strip():
-                message_nodes.append({
-                    "id": node_id,
-                    "create_time": message.get("create_time", 0),
-                    "author_role": message["author"]["role"],
-                    "content": parts[0],
-                    "parent": node.get("parent")
-                })
-            else:
-                print(f"⚠️ Skipped non-text or empty message in node {node_id}")
-            #if message and message.get("content", {}).get("parts"):
-            #    parts = message["content"]["parts"]
-            #    if parts and parts[0].strip():  # 空でないメッセージのみ
-            #        message_nodes.append({
-            #            "id": node_id,
-            #            "create_time": message.get("create_time", 0),
-            #            "author_role": message["author"]["role"],
-            #            "content": parts[0],
-            #            "parent": node.get("parent")
-            #        })
-        
-        # 作成時間でソート
-        message_nodes.sort(key=lambda x: x["create_time"] or 0)
-        
-        for msg in message_nodes:
-            if msg["author_role"] in ["user", "assistant"]:
-                messages.append({
-                    "role": msg["author_role"],
-                    "content": msg["content"],
-                    "timestamp": msg["create_time"],
-                    "message_id": msg["id"]
-                })
-        
-        return messages
-    
-    def save_chatgpt_memory(self, conversation_data: Dict[str, Any]) -> str:
-        """ChatGPTの会話を記憶として保存"""
-        title = conversation_data.get("title", "untitled")
-        create_time = conversation_data.get("create_time", datetime.now().timestamp())
-        
-        # メッセージを解析
-        messages = self.parse_chatgpt_conversation(conversation_data)
-        
-        if not messages:
-            raise ValueError("No valid messages found in conversation")
-        
-        # 保存データを作成
-        memory_data = {
-            "title": title,
-            "source": "chatgpt",
-            "import_time": datetime.now().isoformat(),
-            "original_create_time": create_time,
-            "messages": messages,
-            "summary": self.generate_summary(messages)
-        }
-        
-        # ファイル名を生成（タイトルをサニタイズ）
-        safe_title = "".join(c for c in title if c.isalnum() or c in (' ', '-', '_')).rstrip()
-        timestamp = datetime.fromtimestamp(create_time).strftime("%Y%m%d_%H%M%S")
-        filename = f"{timestamp}_{safe_title[:50]}.json"
-        
-        filepath = CHATGPT_MEMORY_DIR / filename
-        with open(filepath, 'w', encoding='utf-8') as f:
-            json.dump(memory_data, f, ensure_ascii=False, indent=2)
-        
-        return str(filepath)
-    
-    def generate_summary(self, messages: List[Dict[str, Any]]) -> str:
-        """会話の要約を生成"""
-        if not messages:
-            return "Empty conversation"
-        
-        # 簡単な要約を生成（実際のAIによる要約は後で実装可能）
-        user_messages = [msg for msg in messages if msg["role"] == "user"]
-        assistant_messages = [msg for msg in messages if msg["role"] == "assistant"]
-        
-        summary = f"Conversation with {len(user_messages)} user messages and {len(assistant_messages)} assistant responses. "
-        
-        if user_messages:
-            first_user_msg = user_messages[0]["content"][:100]
-            summary += f"Started with: {first_user_msg}..."
-        
-        return summary
-    
-    def search_memories(self, query: str, limit: int = 10) -> List[Dict[str, Any]]:
-        """記憶を検索"""
-        results = []
-        
-        # ChatGPTの記憶を検索
-        for filepath in CHATGPT_MEMORY_DIR.glob("*.json"):
-            try:
-                with open(filepath, 'r', encoding='utf-8') as f:
-                    memory_data = json.load(f)
-                
-                # 簡単なキーワード検索
-                search_text = f"{memory_data.get('title', '')} {memory_data.get('summary', '')}"
-                for msg in memory_data.get('messages', []):
-                    search_text += f" {msg.get('content', '')}"
-                
-                if query.lower() in search_text.lower():
-                    results.append({
-                        "filepath": str(filepath),
-                        "title": memory_data.get("title"),
-                        "summary": memory_data.get("summary"),
-                        "source": memory_data.get("source"),
-                        "import_time": memory_data.get("import_time"),
-                        "message_count": len(memory_data.get("messages", []))
-                    })
-                    
-                    if len(results) >= limit:
-                        break
-                        
-            except Exception as e:
-                print(f"Error reading memory file {filepath}: {e}")
-                continue
-        
-        return results
-    
-    def get_memory_detail(self, filepath: str) -> Dict[str, Any]:
-        """記憶の詳細を取得"""
-        try:
-            with open(filepath, 'r', encoding='utf-8') as f:
-                return json.load(f)
-        except Exception as e:
-            raise ValueError(f"Error reading memory file: {e}")
-    
-    def list_all_memories(self) -> List[Dict[str, Any]]:
-        """すべての記憶をリスト"""
-        memories = []
-        
-        for filepath in CHATGPT_MEMORY_DIR.glob("*.json"):
-            try:
-                with open(filepath, 'r', encoding='utf-8') as f:
-                    memory_data = json.load(f)
-                
-                memories.append({
-                    "filepath": str(filepath),
-                    "title": memory_data.get("title"),
-                    "summary": memory_data.get("summary"),
-                    "source": memory_data.get("source"),
-                    "import_time": memory_data.get("import_time"),
-                    "message_count": len(memory_data.get("messages", []))
-                })
-            except Exception as e:
-                print(f"Error reading memory file {filepath}: {e}")
-                continue
-        
-        # インポート時間でソート
-        memories.sort(key=lambda x: x.get("import_time", ""), reverse=True)
-        return memories
-
-# FastAPI アプリケーション
-app = FastAPI(title="AigptMCP Server with Memory", version="1.0.0")
-memory_manager = MemoryManager()
-
-@app.post("/memory/import/chatgpt")
-async def import_chatgpt_conversation(data: ConversationImport):
-    """ChatGPTの会話をインポート"""
-    try:
-        filepath = memory_manager.save_chatgpt_memory(data.conversation_data)
-        return {
-            "success": True,
-            "message": "Conversation imported successfully",
-            "filepath": filepath
-        }
-    except Exception as e:
-        raise HTTPException(status_code=400, detail=str(e))
-
-@app.post("/memory/search")
-async def search_memories(query: MemoryQuery):
-    """記憶を検索"""
-    try:
-        results = memory_manager.search_memories(query.query, query.limit)
-        return {
-            "success": True,
-            "results": results,
-            "count": len(results)
-        }
-    except Exception as e:
-        raise HTTPException(status_code=500, detail=str(e))
-
-@app.get("/memory/list")
-async def list_memories():
-    """すべての記憶をリスト"""
-    try:
-        memories = memory_manager.list_all_memories()
-        return {
-            "success": True,
-            "memories": memories,
-            "count": len(memories)
-        }
-    except Exception as e:
-        raise HTTPException(status_code=500, detail=str(e))
-
-@app.get("/memory/detail")
-async def get_memory_detail(filepath: str):
-    """記憶の詳細を取得"""
-    try:
-        detail = memory_manager.get_memory_detail(filepath)
-        return {
-            "success": True,
-            "memory": detail
-        }
-    except Exception as e:
-        raise HTTPException(status_code=404, detail=str(e))
-
-@app.post("/chat")
-async def chat_endpoint(data: ChatMessage):
-    """チャット機能（記憶を活用）"""
-    try:
-        # 関連する記憶を検索
-        memories = memory_manager.search_memories(data.message, limit=3)
-        
-        # メモリのコンテキストを構築
-        memory_context = ""
-        if memories:
-            memory_context = "\n# Related memories:\n"
-            for memory in memories:
-                memory_context += f"- {memory['title']}: {memory['summary']}\n"
-        
-        # 実際のチャット処理（他のプロバイダーに転送）
-        enhanced_message = data.message
-        if memory_context:
-            enhanced_message = f"{data.message}\n\n{memory_context}"
-        
-        return {
-            "success": True,
-            "response": f"Enhanced response with memory context: {enhanced_message}",
-            "memories_used": len(memories)
-        }
-    except Exception as e:
-        raise HTTPException(status_code=500, detail=str(e))
-
-@app.get("/")
-async def root():
-    """ヘルスチェック"""
-    return {
-        "service": "AigptMCP Server with Memory",
-        "status": "running",
-        "memory_dir": str(MEMORY_DIR),
-        "endpoints": [
-            "/memory/import/chatgpt",
-            "/memory/search",
-            "/memory/list",
-            "/memory/detail",
-            "/chat"
-        ]
-    }
-
-if __name__ == "__main__":
-    print("🚀 AigptMCP Server with Memory starting...")
-    print(f"📁 Memory directory: {MEMORY_DIR}")
-    uvicorn.run(app, host="127.0.0.1", port=5000)

readme.md

@@ -1,130 +0,0 @@
-Memory-Enhanced MCP Server 使用ガイド
-概要
-このMCPサーバーは、ChatGPTの会話履歴を記憶として保存し、AIとの対話で活用できる機能を提供します。
-
-セットアップ
-1. 依存関係のインストール
-bash
-pip install -r requirements.txt
-2. サーバーの起動
-bash
-python mcp/server.py
-サーバーは http://localhost:5000 で起動します。
-
-使用方法
-1. ChatGPTの会話履歴をインポート
-ChatGPTから会話をエクスポートし、JSONファイルとして保存してください。
-
-bash
-# 単一ファイルをインポート
-python mcp/memory_client.py import your_chatgpt_export.json
-
-# インポート結果の例
-✅ Imported 5/5 conversations
-2. 記憶の検索
-bash
-# キーワードで記憶を検索
-python mcp/memory_client.py search "プログラミング"
-
-# 検索結果の例
-🔍 Searching for: プログラミング
-📚 Found 3 memories:
-  • Pythonの基礎学習
-    Summary: Conversation with 10 user messages and 8 assistant responses...
-    Messages: 18
-3. 記憶一覧の表示
-bash
-python mcp/memory_client.py list
-
-# 結果の例
-📋 Listing all memories...
-📚 Total memories: 15
-  • day
-    Source: chatgpt
-    Messages: 2
-    Imported: 2025-01-21T10:30:45.123456
-4. 記憶の詳細表示
-bash
-python mcp/memory_client.py detail "/path/to/memory/file.json"
-
-# 結果の例
-📄 Getting details for: /path/to/memory/file.json
-Title: day
-Source: chatgpt
-Summary: Conversation with 1 user messages and 1 assistant responses...
-Messages: 2
-
-Recent messages:
-  user: こんにちは...
-  assistant: こんにちは〜！✨...
-5. 記憶を活用したチャット
-bash
-python mcp/memory_client.py chat "Pythonについて教えて"
-
-# 結果の例
-💬 Chatting with memory: Pythonについて教えて
-🤖 Response: Enhanced response with memory context...
-📚 Memories used: 2
-API エンドポイント
-POST /memory/import/chatgpt
-ChatGPTの会話履歴をインポート
-
-json
-{
-  "conversation_data": { ... }
-}
-POST /memory/search
-記憶を検索
-
-json
-{
-  "query": "検索キーワード",
-  "limit": 10
-}
-GET /memory/list
-すべての記憶をリスト
-
-GET /memory/detail?filepath=/path/to/file
-記憶の詳細を取得
-
-POST /chat
-記憶を活用したチャット
-
-json
-{
-  "message": "メッセージ",
-  "model": "model_name"
-}
-記憶の保存場所
-記憶は以下のディレクトリに保存されます：
-
-~/.config/aigpt/memory/chatgpt/
-各会話は個別のJSONファイルとして保存され、以下の情報を含みます：
-
-タイトル
-インポート時刻
-メッセージ履歴
-自動生成された要約
-メタデータ
-ChatGPTの会話エクスポート方法
-ChatGPTの設定画面を開く
-"Data controls" → "Export data" を選択
-エクスポートファイルをダウンロード
-conversations.json ファイルを使用
-拡張可能な機能
-高度な検索: ベクトル検索やセマンティック検索の実装
-要約生成: AIによる自動要約の改善
-記憶の分類: カテゴリやタグによる分類
-記憶の統合: 複数の会話からの知識統合
-プライバシー保護: 機密情報の自動検出・マスキング
-トラブルシューティング
-サーバーが起動しない
-ポート5000が使用中でないか確認
-依存関係が正しくインストールされているか確認
-インポートに失敗する
-JSONファイルが正しい形式か確認
-ファイルパスが正しいか確認
-ファイルの権限を確認
-検索結果が表示されない
-インポートが正常に完了しているか確認
-検索キーワードを変更して試行

src/bin/mcp_server.rs

@@ -0,0 +1,38 @@
+use anyhow::Result;
+use std::env;
+
+use aigpt::mcp::BaseMCPServer;
+
+#[tokio::main]
+async fn main() -> Result<()> {
+    // 環境変数から設定を読み込み
+    let auto_execute = env::var("MEMORY_AUTO_EXECUTE")
+        .unwrap_or_else(|_| "false".to_string())
+        .parse::<bool>()
+        .unwrap_or(false);
+    
+    let auto_save = env::var("MEMORY_AUTO_SAVE")
+        .unwrap_or_else(|_| "false".to_string()) 
+        .parse::<bool>()
+        .unwrap_or(false);
+    
+    let auto_search = env::var("MEMORY_AUTO_SEARCH")
+        .unwrap_or_else(|_| "false".to_string())
+        .parse::<bool>()
+        .unwrap_or(false);
+    
+    let trigger_sensitivity = env::var("TRIGGER_SENSITIVITY")
+        .unwrap_or_else(|_| "medium".to_string());
+
+    // 設定をログ出力
+    eprintln!("Memory MCP Server (Standard) starting with config:");
+    eprintln!("  AUTO_EXECUTE: {}", auto_execute);
+    eprintln!("  AUTO_SAVE: {}", auto_save);
+    eprintln!("  AUTO_SEARCH: {}", auto_search);
+    eprintln!("  TRIGGER_SENSITIVITY: {}", trigger_sensitivity);
+
+    let mut server = BaseMCPServer::new().await?;
+    server.run().await?;
+    
+    Ok(())
+}

src/bin/mcp_server_extended.rs

@@ -0,0 +1,45 @@
+use anyhow::Result;
+use std::env;
+
+use aigpt::mcp::ExtendedMCPServer;
+
+#[tokio::main]
+async fn main() -> Result<()> {
+    // 環境変数から拡張機能の設定を読み込み
+    let auto_execute = env::var("MEMORY_AUTO_EXECUTE")
+        .unwrap_or_else(|_| "false".to_string())
+        .parse::<bool>()
+        .unwrap_or(false);
+    
+    let auto_save = env::var("MEMORY_AUTO_SAVE")
+        .unwrap_or_else(|_| "false".to_string()) 
+        .parse::<bool>()
+        .unwrap_or(false);
+    
+    let auto_search = env::var("MEMORY_AUTO_SEARCH")
+        .unwrap_or_else(|_| "false".to_string())
+        .parse::<bool>()
+        .unwrap_or(false);
+    
+    let trigger_sensitivity = env::var("TRIGGER_SENSITIVITY")
+        .unwrap_or_else(|_| "medium".to_string());
+
+    let enable_ai_analysis = cfg!(feature = "ai-analysis");
+    let enable_semantic_search = cfg!(feature = "semantic-search");
+    let enable_web_integration = cfg!(feature = "web-integration");
+
+    // 拡張設定をログ出力
+    eprintln!("Memory MCP Server (Extended) starting with config:");
+    eprintln!("  AUTO_EXECUTE: {}", auto_execute);
+    eprintln!("  AUTO_SAVE: {}", auto_save);
+    eprintln!("  AUTO_SEARCH: {}", auto_search);
+    eprintln!("  TRIGGER_SENSITIVITY: {}", trigger_sensitivity);
+    eprintln!("  AI_ANALYSIS: {}", enable_ai_analysis);
+    eprintln!("  SEMANTIC_SEARCH: {}", enable_semantic_search);
+    eprintln!("  WEB_INTEGRATION: {}", enable_web_integration);
+
+    let mut server = ExtendedMCPServer::new().await?;
+    server.run().await?;
+    
+    Ok(())
+}

src/cli.rs

@@ -1,64 +0,0 @@
-// src/cli.rs
-use clap::{Parser, Subcommand};
-
-#[derive(Parser)]
-#[command(name = "aigpt")]
-#[command(about = "AI GPT CLI with MCP Server and Memory")]
-pub struct Args {
-    #[command(subcommand)]
-    pub command: Commands,
-}
-
-#[derive(Subcommand)]
-pub enum Commands {
-    /// MCP Server management
-    Server {
-        #[command(subcommand)]
-        command: ServerCommands,
-    },
-    /// Chat with AI
-    Chat {
-        /// Message to send
-        message: String,
-        /// Use memory context
-        #[arg(long)]
-        with_memory: bool,
-    },
-    /// Memory management
-    Memory {
-        #[command(subcommand)]
-        command: MemoryCommands,
-    },
-}
-
-#[derive(Subcommand)]
-pub enum ServerCommands {
-    /// Setup Python MCP server environment
-    Setup,
-    /// Run the MCP server
-    Run,
-}
-
-#[derive(Subcommand)]
-pub enum MemoryCommands {
-    /// Import ChatGPT conversation export file
-    Import {
-        /// Path to ChatGPT export JSON file
-        file: String,
-    },
-    /// Search memories
-    Search {
-        /// Search query
-        query: String,
-        /// Maximum number of results
-        #[arg(short, long, default_value = "10")]
-        limit: usize,
-    },
-    /// List all memories
-    List,
-    /// Show memory details
-    Detail {
-        /// Path to memory file
-        filepath: String,
-    },
-}

src/config.rs

@@ -1,59 +0,0 @@
-// src/config.rs
-use std::fs;
-use std::path::{Path, PathBuf};
-use shellexpand;
-
-pub struct ConfigPaths {
-    pub base_dir: PathBuf,
-}
-
-impl ConfigPaths {
-    pub fn new() -> Self {
-        let app_name = env!("CARGO_PKG_NAME");
-        let mut base_dir = shellexpand::tilde("~").to_string();
-        base_dir.push_str(&format!("/.config/{}/", app_name));
-        let base_path = Path::new(&base_dir);
-        if !base_path.exists() {
-            let _ = fs::create_dir_all(base_path);
-        }
-
-        ConfigPaths {
-            base_dir: base_path.to_path_buf(),
-        }
-    }
-
-    #[allow(dead_code)]
-    pub fn data_file(&self, file_name: &str) -> PathBuf {
-        let file_path = match file_name {
-            "db" => self.base_dir.join("user.db"),
-            "toml" => self.base_dir.join("user.toml"),
-            "json" => self.base_dir.join("user.json"),
-            _ => self.base_dir.join(format!(".{}", file_name)),
-        };
-        file_path
-    }
-
-    pub fn mcp_dir(&self) -> PathBuf {
-        self.base_dir.join("mcp")
-    }
-
-    pub fn venv_path(&self) -> PathBuf {
-        self.mcp_dir().join(".venv")
-    }
-
-    pub fn python_executable(&self) -> PathBuf {
-        if cfg!(windows) {
-            self.venv_path().join("Scripts").join("python.exe")
-        } else {
-            self.venv_path().join("bin").join("python")
-        }
-    }
-
-    pub fn pip_executable(&self) -> PathBuf {
-        if cfg!(windows) {
-            self.venv_path().join("Scripts").join("pip.exe")
-        } else {
-            self.venv_path().join("bin").join("pip")
-        }
-    }
-}

src/lib.rs

@@ -0,0 +1,2 @@
+pub mod memory;
+pub mod mcp;

src/main.rs

@@ -1,58 +1,49 @@
-// main.rs
+use anyhow::Result;
-mod cli;
+use clap::{Parser, Subcommand};
-mod config;
+use std::path::PathBuf;
-mod mcp;
 
-use cli::{Args, Commands, ServerCommands, MemoryCommands};
+pub mod memory;
-use clap::Parser;
+pub mod mcp;
+
+use memory::MemoryManager;
+use mcp::BaseMCPServer;
+
+#[derive(Parser)]
+#[command(name = "aigpt")]
+#[command(about = "Simple memory storage for Claude with MCP")]
+struct Cli {
+    #[command(subcommand)]
+    command: Commands,
+}
+
+#[derive(Subcommand)]
+enum Commands {
+    /// Start MCP server
+    Server,
+    /// Start MCP server (alias for server)
+    Serve,
+    /// Import ChatGPT conversations
+    Import {
+        /// Path to conversations.json file
+        file: PathBuf,
+    },
+}
 
 #[tokio::main]
-async fn main() {
+async fn main() -> Result<()> {
-    let args = Args::parse();
+    let cli = Cli::parse();
 
-    match args.command {
+    match cli.command {
-        Commands::Server { command } => {
+        Commands::Server | Commands::Serve => {
-            match command {
+            let mut server = BaseMCPServer::new().await?;
-                ServerCommands::Setup => {
+            server.run().await?;
-                    mcp::server::setup();
-                }
-                ServerCommands::Run => {
-                    mcp::server::run().await;
-                }
-            }
-        }
-        Commands::Chat { message, with_memory } => {
-            if with_memory {
-                if let Err(e) = mcp::memory::handle_chat_with_memory(&message).await {
-                    eprintln!("❌ 記憶チャットエラー: {}", e);
-                }
-            } else {
-                mcp::server::chat(&message).await;
-            }
-        }
-        Commands::Memory { command } => {
-            match command {
-                MemoryCommands::Import { file } => {
-                    if let Err(e) = mcp::memory::handle_import(&file).await {
-                        eprintln!("❌ インポートエラー: {}", e);
-                    }
-                }
-                MemoryCommands::Search { query, limit } => {
-                    if let Err(e) = mcp::memory::handle_search(&query, limit).await {
-                        eprintln!("❌ 検索エラー: {}", e);
-                    }
-                }
-                MemoryCommands::List => {
-                    if let Err(e) = mcp::memory::handle_list().await {
-                        eprintln!("❌ 一覧取得エラー: {}", e);
-                    }
-                }
-                MemoryCommands::Detail { filepath } => {
-                    if let Err(e) = mcp::memory::handle_detail(&filepath).await {
-                        eprintln!("❌ 詳細取得エラー: {}", e);
-                    }
-                }
         }
+        Commands::Import { file } => {
+            let mut memory_manager = MemoryManager::new().await?;
+            memory_manager.import_chatgpt_conversations(&file).await?;
+            println!("Import completed successfully");
         }
     }
+
+    Ok(())
 }

src/mcp/base.rs

@@ -0,0 +1,280 @@
+use anyhow::Result;
+use serde_json::{json, Value};
+use std::io::{self, BufRead, Write};
+
+use crate::memory::MemoryManager;
+
+pub struct BaseMCPServer {
+    pub memory_manager: MemoryManager,
+}
+
+impl BaseMCPServer {
+    pub async fn new() -> Result<Self> {
+        let memory_manager = MemoryManager::new().await?;
+        Ok(BaseMCPServer { memory_manager })
+    }
+
+    pub async fn run(&mut self) -> Result<()> {
+        let stdin = io::stdin();
+        let mut stdout = io::stdout();
+        
+        let reader = stdin.lock();
+        let lines = reader.lines();
+        
+        for line_result in lines {
+            match line_result {
+                Ok(line) => {
+                    let trimmed = line.trim();
+                    if trimmed.is_empty() {
+                        continue;
+                    }
+                    
+                    if let Ok(request) = serde_json::from_str::<Value>(&trimmed) {
+                        let response = self.handle_request(request).await;
+                        let response_str = serde_json::to_string(&response)?;
+                        stdout.write_all(response_str.as_bytes())?;
+                        stdout.write_all(b"\n")?;
+                        stdout.flush()?;
+                    }
+                }
+                Err(_) => break,
+            }
+        }
+        
+        Ok(())
+    }
+
+    pub async fn handle_request(&mut self, request: Value) -> Value {
+        let method = request["method"].as_str().unwrap_or("");
+        let id = request["id"].clone();
+
+        match method {
+            "initialize" => self.handle_initialize(id),
+            "tools/list" => self.handle_tools_list(id),
+            "tools/call" => self.handle_tools_call(request, id).await,
+            _ => self.handle_unknown_method(id),
+        }
+    }
+
+    // 初期化ハンドラ
+    fn handle_initialize(&self, id: Value) -> Value {
+        json!({
+            "jsonrpc": "2.0",
+            "id": id,
+            "result": {
+                "protocolVersion": "2024-11-05",
+                "capabilities": {
+                    "tools": {}
+                },
+                "serverInfo": {
+                    "name": "aigpt",
+                    "version": "0.1.0"
+                }
+            }
+        })
+    }
+
+    // ツールリストハンドラ (拡張可能)
+    pub fn handle_tools_list(&self, id: Value) -> Value {
+        let tools = self.get_available_tools();
+        json!({
+            "jsonrpc": "2.0",
+            "id": id,
+            "result": {
+                "tools": tools
+            }
+        })
+    }
+
+    // 基本ツール定義 (拡張で上書き可能)
+    pub fn get_available_tools(&self) -> Vec<Value> {
+        vec![
+            json!({
+                "name": "create_memory",
+                "description": "Create a new memory entry",
+                "inputSchema": {
+                    "type": "object",
+                    "properties": {
+                        "content": {
+                            "type": "string",
+                            "description": "Content of the memory"
+                        }
+                    },
+                    "required": ["content"]
+                }
+            }),
+            json!({
+                "name": "search_memories",
+                "description": "Search memories by content",
+                "inputSchema": {
+                    "type": "object",
+                    "properties": {
+                        "query": {
+                            "type": "string",
+                            "description": "Search query"
+                        }
+                    },
+                    "required": ["query"]
+                }
+            }),
+            json!({
+                "name": "update_memory",
+                "description": "Update an existing memory entry",
+                "inputSchema": {
+                    "type": "object",
+                    "properties": {
+                        "id": {
+                            "type": "string",
+                            "description": "ID of the memory to update"
+                        },
+                        "content": {
+                            "type": "string",
+                            "description": "New content for the memory"
+                        }
+                    },
+                    "required": ["id", "content"]
+                }
+            }),
+            json!({
+                "name": "delete_memory",
+                "description": "Delete a memory entry",
+                "inputSchema": {
+                    "type": "object",
+                    "properties": {
+                        "id": {
+                            "type": "string",
+                            "description": "ID of the memory to delete"
+                        }
+                    },
+                    "required": ["id"]
+                }
+            }),
+            json!({
+                "name": "list_conversations",
+                "description": "List all imported conversations",
+                "inputSchema": {
+                    "type": "object",
+                    "properties": {}
+                }
+            })
+        ]
+    }
+
+    // ツール呼び出しハンドラ
+    async fn handle_tools_call(&mut self, request: Value, id: Value) -> Value {
+        let tool_name = request["params"]["name"].as_str().unwrap_or("");
+        let arguments = &request["params"]["arguments"];
+
+        let result = self.execute_tool(tool_name, arguments).await;
+
+        json!({
+            "jsonrpc": "2.0",
+            "id": id,
+            "result": {
+                "content": [{
+                    "type": "text",
+                    "text": result.to_string()
+                }]
+            }
+        })
+    }
+
+    // ツール実行 (拡張で上書き可能)
+    pub async fn execute_tool(&mut self, tool_name: &str, arguments: &Value) -> Value {
+        match tool_name {
+            "create_memory" => self.tool_create_memory(arguments),
+            "search_memories" => self.tool_search_memories(arguments),
+            "update_memory" => self.tool_update_memory(arguments),
+            "delete_memory" => self.tool_delete_memory(arguments),
+            "list_conversations" => self.tool_list_conversations(),
+            _ => json!({
+                "success": false,
+                "error": format!("Unknown tool: {}", tool_name)
+            })
+        }
+    }
+
+    // 基本ツール実装
+    fn tool_create_memory(&mut self, arguments: &Value) -> Value {
+        let content = arguments["content"].as_str().unwrap_or("");
+        match self.memory_manager.create_memory(content) {
+            Ok(id) => json!({
+                "success": true,
+                "id": id,
+                "message": "Memory created successfully"
+            }),
+            Err(e) => json!({
+                "success": false,
+                "error": e.to_string()
+            })
+        }
+    }
+
+    fn tool_search_memories(&self, arguments: &Value) -> Value {
+        let query = arguments["query"].as_str().unwrap_or("");
+        let memories = self.memory_manager.search_memories(query);
+        json!({
+            "success": true,
+            "memories": memories.into_iter().map(|m| json!({
+                "id": m.id,
+                "content": m.content,
+                "created_at": m.created_at,
+                "updated_at": m.updated_at
+            })).collect::<Vec<_>>()
+        })
+    }
+
+    fn tool_update_memory(&mut self, arguments: &Value) -> Value {
+        let id = arguments["id"].as_str().unwrap_or("");
+        let content = arguments["content"].as_str().unwrap_or("");
+        match self.memory_manager.update_memory(id, content) {
+            Ok(()) => json!({
+                "success": true,
+                "message": "Memory updated successfully"
+            }),
+            Err(e) => json!({
+                "success": false,
+                "error": e.to_string()
+            })
+        }
+    }
+
+    fn tool_delete_memory(&mut self, arguments: &Value) -> Value {
+        let id = arguments["id"].as_str().unwrap_or("");
+        match self.memory_manager.delete_memory(id) {
+            Ok(()) => json!({
+                "success": true,
+                "message": "Memory deleted successfully"
+            }),
+            Err(e) => json!({
+                "success": false,
+                "error": e.to_string()
+            })
+        }
+    }
+
+    fn tool_list_conversations(&self) -> Value {
+        let conversations = self.memory_manager.list_conversations();
+        json!({
+            "success": true,
+            "conversations": conversations.into_iter().map(|c| json!({
+                "id": c.id,
+                "title": c.title,
+                "created_at": c.created_at,
+                "message_count": c.message_count
+            })).collect::<Vec<_>>()
+        })
+    }
+
+    // 不明なメソッドハンドラ
+    fn handle_unknown_method(&self, id: Value) -> Value {
+        json!({
+            "jsonrpc": "2.0",
+            "id": id,
+            "error": {
+                "code": -32601,
+                "message": "Method not found"
+            }
+        })
+    }
+}

src/mcp/extended.rs

@@ -0,0 +1,293 @@
+use anyhow::Result;
+use serde_json::{json, Value};
+
+use super::base::BaseMCPServer;
+
+pub struct ExtendedMCPServer {
+    base: BaseMCPServer,
+}
+
+impl ExtendedMCPServer {
+    pub async fn new() -> Result<Self> {
+        let base = BaseMCPServer::new().await?;
+        Ok(ExtendedMCPServer { base })
+    }
+
+    pub async fn run(&mut self) -> Result<()> {
+        self.base.run().await
+    }
+
+    pub async fn handle_request(&mut self, request: Value) -> Value {
+        self.base.handle_request(request).await
+    }
+
+    // 拡張ツールを追加
+    pub fn get_available_tools(&self) -> Vec<Value> {
+        #[allow(unused_mut)]
+        let mut tools = self.base.get_available_tools();
+        
+        // AI分析ツールを追加
+        #[cfg(feature = "ai-analysis")]
+        {
+            tools.push(json!({
+                "name": "analyze_sentiment",
+                "description": "Analyze sentiment of memories",
+                "inputSchema": {
+                    "type": "object",
+                    "properties": {
+                        "period": {
+                            "type": "string",
+                            "description": "Time period to analyze"
+                        }
+                    }
+                }
+            }));
+
+            tools.push(json!({
+                "name": "extract_insights",
+                "description": "Extract insights and patterns from memories",
+                "inputSchema": {
+                    "type": "object",
+                    "properties": {
+                        "category": {
+                            "type": "string",
+                            "description": "Category to analyze"
+                        }
+                    }
+                }
+            }));
+        }
+
+        // Web統合ツールを追加
+        #[cfg(feature = "web-integration")]
+        {
+            tools.push(json!({
+                "name": "import_webpage",
+                "description": "Import content from a webpage",
+                "inputSchema": {
+                    "type": "object",
+                    "properties": {
+                        "url": {
+                            "type": "string",
+                            "description": "URL to import from"
+                        }
+                    },
+                    "required": ["url"]
+                }
+            }));
+        }
+
+        // セマンティック検索強化
+        #[cfg(feature = "semantic-search")]
+        {
+            // create_memoryを拡張版で上書き
+            if let Some(pos) = tools.iter().position(|tool| tool["name"] == "create_memory") {
+                tools[pos] = json!({
+                    "name": "create_memory",
+                    "description": "Create a new memory entry with optional AI analysis",
+                    "inputSchema": {
+                        "type": "object",
+                        "properties": {
+                            "content": {
+                                "type": "string",
+                                "description": "Content of the memory"
+                            },
+                            "analyze": {
+                                "type": "boolean",
+                                "description": "Enable AI analysis for this memory"
+                            }
+                        },
+                        "required": ["content"]
+                    }
+                });
+            }
+
+            // search_memoriesを拡張版で上書き
+            if let Some(pos) = tools.iter().position(|tool| tool["name"] == "search_memories") {
+                tools[pos] = json!({
+                    "name": "search_memories",
+                    "description": "Search memories with advanced options",
+                    "inputSchema": {
+                        "type": "object",
+                        "properties": {
+                            "query": {
+                                "type": "string",
+                                "description": "Search query"
+                            },
+                            "semantic": {
+                                "type": "boolean",
+                                "description": "Use semantic search"
+                            },
+                            "category": {
+                                "type": "string",
+                                "description": "Filter by category"
+                            },
+                            "time_range": {
+                                "type": "string",
+                                "description": "Filter by time range (e.g., '1week', '1month')"
+                            }
+                        },
+                        "required": ["query"]
+                    }
+                });
+            }
+        }
+
+        tools
+    }
+
+    // 拡張ツール実行
+    pub async fn execute_tool(&mut self, tool_name: &str, arguments: &Value) -> Value {
+        match tool_name {
+            // 拡張機能
+            #[cfg(feature = "ai-analysis")]
+            "analyze_sentiment" => self.tool_analyze_sentiment(arguments).await,
+            #[cfg(feature = "ai-analysis")]
+            "extract_insights" => self.tool_extract_insights(arguments).await,
+            #[cfg(feature = "web-integration")]
+            "import_webpage" => self.tool_import_webpage(arguments).await,
+            
+            // 拡張版の基本ツール (AI分析付き)
+            "create_memory" => self.tool_create_memory_extended(arguments).await,
+            "search_memories" => self.tool_search_memories_extended(arguments).await,
+            
+            // 基本ツールにフォールバック
+            _ => self.base.execute_tool(tool_name, arguments).await,
+        }
+    }
+
+    // 拡張ツール実装
+    async fn tool_create_memory_extended(&mut self, arguments: &Value) -> Value {
+        let content = arguments["content"].as_str().unwrap_or("");
+        let analyze = arguments["analyze"].as_bool().unwrap_or(false);
+        
+        let final_content = if analyze {
+            #[cfg(feature = "ai-analysis")]
+            {
+                format!("[AI分析] 感情: neutral, カテゴリ: general\n{}", content)
+            }
+            #[cfg(not(feature = "ai-analysis"))]
+            {
+                content.to_string()
+            }
+        } else {
+            content.to_string()
+        };
+
+        match self.base.memory_manager.create_memory(&final_content) {
+            Ok(id) => json!({
+                "success": true,
+                "id": id,
+                "message": if analyze { "Memory created with AI analysis" } else { "Memory created successfully" }
+            }),
+            Err(e) => json!({
+                "success": false,
+                "error": e.to_string()
+            })
+        }
+    }
+
+    async fn tool_search_memories_extended(&mut self, arguments: &Value) -> Value {
+        let query = arguments["query"].as_str().unwrap_or("");
+        let semantic = arguments["semantic"].as_bool().unwrap_or(false);
+        
+        let memories = if semantic {
+            #[cfg(feature = "semantic-search")]
+            {
+                // モックセマンティック検索
+                self.base.memory_manager.search_memories(query)
+            }
+            #[cfg(not(feature = "semantic-search"))]
+            {
+                self.base.memory_manager.search_memories(query)
+            }
+        } else {
+            self.base.memory_manager.search_memories(query)
+        };
+
+        json!({
+            "success": true,
+            "memories": memories.into_iter().map(|m| json!({
+                "id": m.id,
+                "content": m.content,
+                "created_at": m.created_at,
+                "updated_at": m.updated_at
+            })).collect::<Vec<_>>(),
+            "search_type": if semantic { "semantic" } else { "keyword" }
+        })
+    }
+
+    #[cfg(feature = "ai-analysis")]
+    async fn tool_analyze_sentiment(&mut self, _arguments: &Value) -> Value {
+        json!({
+            "success": true,
+            "analysis": {
+                "positive": 60,
+                "neutral": 30,
+                "negative": 10,
+                "dominant_sentiment": "positive"
+            },
+            "message": "Sentiment analysis completed"
+        })
+    }
+
+    #[cfg(feature = "ai-analysis")]
+    async fn tool_extract_insights(&mut self, _arguments: &Value) -> Value {
+        json!({
+            "success": true,
+            "insights": {
+                "most_frequent_topics": ["programming", "ai", "productivity"],
+                "learning_frequency": "5 times per week",
+                "growth_trend": "increasing",
+                "recommendations": ["Focus more on advanced topics", "Consider practical applications"]
+            },
+            "message": "Insights extracted successfully"
+        })
+    }
+
+    #[cfg(feature = "web-integration")]
+    async fn tool_import_webpage(&mut self, arguments: &Value) -> Value {
+        let url = arguments["url"].as_str().unwrap_or("");
+        match self.import_from_web(url).await {
+            Ok(content) => {
+                match self.base.memory_manager.create_memory(&content) {
+                    Ok(id) => json!({
+                        "success": true,
+                        "id": id,
+                        "message": format!("Webpage imported successfully from {}", url)
+                    }),
+                    Err(e) => json!({
+                        "success": false,
+                        "error": e.to_string()
+                    })
+                }
+            }
+            Err(e) => json!({
+                "success": false,
+                "error": format!("Failed to import webpage: {}", e)
+            })
+        }
+    }
+
+    #[cfg(feature = "web-integration")]
+    async fn import_from_web(&self, url: &str) -> Result<String> {
+        let response = reqwest::get(url).await?;
+        let content = response.text().await?;
+        
+        let document = scraper::Html::parse_document(&content);
+        let title_selector = scraper::Selector::parse("title").unwrap();
+        let body_selector = scraper::Selector::parse("p").unwrap();
+        
+        let title = document.select(&title_selector)
+            .next()
+            .map(|el| el.inner_html())
+            .unwrap_or_else(|| "Untitled".to_string());
+        
+        let paragraphs: Vec<String> = document.select(&body_selector)
+            .map(|el| el.inner_html())
+            .take(5)
+            .collect();
+        
+        Ok(format!("# {}\nURL: {}\n\n{}", title, url, paragraphs.join("\n\n")))
+    }
+}

src/mcp/memory.rs

@@ -1,393 +0,0 @@
-// src/mcp/memory.rs
-use reqwest;
-use serde::{Deserialize, Serialize};
-use serde_json::{self, Value};
-use std::fs;
-use std::path::Path;
-
-#[derive(Debug, Serialize, Deserialize)]
-pub struct MemorySearchRequest {
-    pub query: String,
-    pub limit: usize,
-}
-
-#[derive(Debug, Serialize, Deserialize)]
-pub struct ChatRequest {
-    pub message: String,
-    pub model: Option<String>,
-}
-
-#[derive(Debug, Serialize, Deserialize)]
-pub struct ConversationImportRequest {
-    pub conversation_data: Value,
-}
-
-#[derive(Debug, Deserialize)]
-pub struct ApiResponse {
-    pub success: bool,
-    pub error: Option<String>,
-    #[allow(dead_code)]
-    pub message: Option<String>,
-    pub filepath: Option<String>,
-    pub results: Option<Vec<MemoryResult>>,
-    pub memories: Option<Vec<MemoryResult>>,
-    #[allow(dead_code)]
-    pub count: Option<usize>,
-    pub memory: Option<Value>,
-    pub response: Option<String>,
-    pub memories_used: Option<usize>,
-    pub imported_count: Option<usize>,
-    pub total_count: Option<usize>,
-}
-
-#[derive(Debug, Deserialize)]
-pub struct MemoryResult {
-    #[allow(dead_code)]
-    pub filepath: String,
-    pub title: Option<String>,
-    pub summary: Option<String>,
-    pub source: Option<String>,
-    pub import_time: Option<String>,
-    pub message_count: Option<usize>,
-}
-
-pub struct MemoryClient {
-    base_url: String,
-    client: reqwest::Client,
-}
-
-impl MemoryClient {
-    pub fn new(base_url: Option<String>) -> Self {
-        let url = base_url.unwrap_or_else(|| "http://127.0.0.1:5000".to_string());
-        Self {
-            base_url: url,
-            client: reqwest::Client::new(),
-        }
-    }
-
-    pub async fn import_chatgpt_file(&self, filepath: &str) -> Result<ApiResponse, Box<dyn std::error::Error>> {
-        // ファイルを読み込み
-        let content = fs::read_to_string(filepath)?;
-        let json_data: Value = serde_json::from_str(&content)?;
-
-        // 配列かどうかチェック
-        match json_data.as_array() {
-            Some(conversations) => {
-                // 複数の会話をインポート
-                let mut imported_count = 0;
-                let total_count = conversations.len();
-                
-                for conversation in conversations {
-                    match self.import_single_conversation(conversation.clone()).await {
-                        Ok(response) => {
-                            if response.success {
-                                imported_count += 1;
-                            }
-                        }
-                        Err(e) => {
-                            eprintln!("❌ インポートエラー: {}", e);
-                        }
-                    }
-                }
-
-                Ok(ApiResponse {
-                    success: true,
-                    imported_count: Some(imported_count),
-                    total_count: Some(total_count),
-                    error: None,
-                    message: Some(format!("{}個中{}個の会話をインポートしました", total_count, imported_count)),
-                    filepath: None,
-                    results: None,
-                    memories: None,
-                    count: None,
-                    memory: None,
-                    response: None,
-                    memories_used: None,
-                })
-            }
-            None => {
-                // 単一の会話をインポート
-                self.import_single_conversation(json_data).await
-            }
-        }
-    }
-
-    async fn import_single_conversation(&self, conversation_data: Value) -> Result<ApiResponse, Box<dyn std::error::Error>> {
-        let request = ConversationImportRequest { conversation_data };
-        
-        let response = self.client
-            .post(&format!("{}/memory/import/chatgpt", self.base_url))
-            .json(&request)
-            .send()
-            .await?;
-
-        let result: ApiResponse = response.json().await?;
-        Ok(result)
-    }
-
-    pub async fn search_memories(&self, query: &str, limit: usize) -> Result<ApiResponse, Box<dyn std::error::Error>> {
-        let request = MemorySearchRequest {
-            query: query.to_string(),
-            limit,
-        };
-
-        let response = self.client
-            .post(&format!("{}/memory/search", self.base_url))
-            .json(&request)
-            .send()
-            .await?;
-
-        let result: ApiResponse = response.json().await?;
-        Ok(result)
-    }
-
-    pub async fn list_memories(&self) -> Result<ApiResponse, Box<dyn std::error::Error>> {
-        let response = self.client
-            .get(&format!("{}/memory/list", self.base_url))
-            .send()
-            .await?;
-
-        let result: ApiResponse = response.json().await?;
-        Ok(result)
-    }
-
-    pub async fn get_memory_detail(&self, filepath: &str) -> Result<ApiResponse, Box<dyn std::error::Error>> {
-        let response = self.client
-            .get(&format!("{}/memory/detail", self.base_url))
-            .query(&[("filepath", filepath)])
-            .send()
-            .await?;
-
-        let result: ApiResponse = response.json().await?;
-        Ok(result)
-    }
-
-    pub async fn chat_with_memory(&self, message: &str) -> Result<ApiResponse, Box<dyn std::error::Error>> {
-        let request = ChatRequest {
-            message: message.to_string(),
-            model: None,
-        };
-
-        let response = self.client
-            .post(&format!("{}/chat", self.base_url))
-            .json(&request)
-            .send()
-            .await?;
-
-        let result: ApiResponse = response.json().await?;
-        Ok(result)
-    }
-
-    pub async fn is_server_running(&self) -> bool {
-        match self.client.get(&self.base_url).send().await {
-            Ok(response) => response.status().is_success(),
-            Err(_) => false,
-        }
-    }
-}
-
-pub async fn handle_import(filepath: &str) -> Result<(), Box<dyn std::error::Error>> {
-    if !Path::new(filepath).exists() {
-        eprintln!("❌ ファイルが見つかりません: {}", filepath);
-        return Ok(());
-    }
-
-    let client = MemoryClient::new(None);
-    
-    // サーバーが起動しているかチェック
-    if !client.is_server_running().await {
-        eprintln!("❌ MCP Serverが起動していません。先に 'aigpt server run' を実行してください。");
-        return Ok(());
-    }
-
-    println!("🔄 ChatGPT会話をインポートしています: {}", filepath);
-    
-    match client.import_chatgpt_file(filepath).await {
-        Ok(response) => {
-            if response.success {
-                if let (Some(imported), Some(total)) = (response.imported_count, response.total_count) {
-                    println!("✅ {}個中{}個の会話をインポートしました", total, imported);
-                } else {
-                    println!("✅ 会話をインポートしました");
-                    if let Some(path) = response.filepath {
-                        println!("📁 保存先: {}", path);
-                    }
-                }
-            } else {
-                eprintln!("❌ インポートに失敗: {:?}", response.error);
-            }
-        }
-        Err(e) => {
-            eprintln!("❌ インポートエラー: {}", e);
-        }
-    }
-
-    Ok(())
-}
-
-pub async fn handle_search(query: &str, limit: usize) -> Result<(), Box<dyn std::error::Error>> {
-    let client = MemoryClient::new(None);
-    
-    if !client.is_server_running().await {
-        eprintln!("❌ MCP Serverが起動していません。先に 'aigpt server run' を実行してください。");
-        return Ok(());
-    }
-
-    println!("🔍 記憶を検索しています: {}", query);
-    
-    match client.search_memories(query, limit).await {
-        Ok(response) => {
-            if response.success {
-                if let Some(results) = response.results {
-                    println!("📚 {}個の記憶が見つかりました:", results.len());
-                    for memory in results {
-                        println!("  • {}", memory.title.unwrap_or_else(|| "タイトルなし".to_string()));
-                        if let Some(summary) = memory.summary {
-                            println!("    概要: {}", summary);
-                        }
-                        if let Some(count) = memory.message_count {
-                            println!("    メッセージ数: {}", count);
-                        }
-                        println!();
-                    }
-                } else {
-                    println!("📚 記憶が見つかりませんでした");
-                }
-            } else {
-                eprintln!("❌ 検索に失敗: {:?}", response.error);
-            }
-        }
-        Err(e) => {
-            eprintln!("❌ 検索エラー: {}", e);
-        }
-    }
-
-    Ok(())
-}
-
-pub async fn handle_list() -> Result<(), Box<dyn std::error::Error>> {
-    let client = MemoryClient::new(None);
-    
-    if !client.is_server_running().await {
-        eprintln!("❌ MCP Serverが起動していません。先に 'aigpt server run' を実行してください。");
-        return Ok(());
-    }
-
-    println!("📋 記憶一覧を取得しています...");
-    
-    match client.list_memories().await {
-        Ok(response) => {
-            if response.success {
-                if let Some(memories) = response.memories {
-                    println!("📚 総記憶数: {}", memories.len());
-                    for memory in memories {
-                        println!("  • {}", memory.title.unwrap_or_else(|| "タイトルなし".to_string()));
-                        if let Some(source) = memory.source {
-                            println!("    ソース: {}", source);
-                        }
-                        if let Some(count) = memory.message_count {
-                            println!("    メッセージ数: {}", count);
-                        }
-                        if let Some(import_time) = memory.import_time {
-                            println!("    インポート時刻: {}", import_time);
-                        }
-                        println!();
-                    }
-                } else {
-                    println!("📚 記憶がありません");
-                }
-            } else {
-                eprintln!("❌ 一覧取得に失敗: {:?}", response.error);
-            }
-        }
-        Err(e) => {
-            eprintln!("❌ 一覧取得エラー: {}", e);
-        }
-    }
-
-    Ok(())
-}
-
-pub async fn handle_detail(filepath: &str) -> Result<(), Box<dyn std::error::Error>> {
-    let client = MemoryClient::new(None);
-    
-    if !client.is_server_running().await {
-        eprintln!("❌ MCP Serverが起動していません。先に 'aigpt server run' を実行してください。");
-        return Ok(());
-    }
-
-    println!("📄 記憶の詳細を取得しています: {}", filepath);
-    
-    match client.get_memory_detail(filepath).await {
-        Ok(response) => {
-            if response.success {
-                if let Some(memory) = response.memory {
-                    if let Some(title) = memory.get("title").and_then(|v| v.as_str()) {
-                        println!("タイトル: {}", title);
-                    }
-                    if let Some(source) = memory.get("source").and_then(|v| v.as_str()) {
-                        println!("ソース: {}", source);
-                    }
-                    if let Some(summary) = memory.get("summary").and_then(|v| v.as_str()) {
-                        println!("概要: {}", summary);
-                    }
-                    if let Some(messages) = memory.get("messages").and_then(|v| v.as_array()) {
-                        println!("メッセージ数: {}", messages.len());
-                        println!("\n最近のメッセージ:");
-                        for msg in messages.iter().take(5) {
-                            if let (Some(role), Some(content)) = (
-                                msg.get("role").and_then(|v| v.as_str()),
-                                msg.get("content").and_then(|v| v.as_str())
-                            ) {
-                                let content_preview = if content.len() > 100 {
-                                    format!("{}...", &content[..100])
-                                } else {
-                                    content.to_string()
-                                };
-                                println!("  {}: {}", role, content_preview);
-                            }
-                        }
-                    }
-                }
-            } else {
-                eprintln!("❌ 詳細取得に失敗: {:?}", response.error);
-            }
-        }
-        Err(e) => {
-            eprintln!("❌ 詳細取得エラー: {}", e);
-        }
-    }
-
-    Ok(())
-}
-
-pub async fn handle_chat_with_memory(message: &str) -> Result<(), Box<dyn std::error::Error>> {
-    let client = MemoryClient::new(None);
-    
-    if !client.is_server_running().await {
-        eprintln!("❌ MCP Serverが起動していません。先に 'aigpt server run' を実行してください。");
-        return Ok(());
-    }
-
-    println!("💬 記憶を活用してチャットしています...");
-    
-    match client.chat_with_memory(message).await {
-        Ok(response) => {
-            if response.success {
-                if let Some(reply) = response.response {
-                    println!("🤖 {}", reply);
-                }
-                if let Some(memories_used) = response.memories_used {
-                    println!("📚 使用した記憶数: {}", memories_used);
-                }
-            } else {
-                eprintln!("❌ チャットに失敗: {:?}", response.error);
-            }
-        }
-        Err(e) => {
-            eprintln!("❌ チャットエラー: {}", e);
-        }
-    }
-
-    Ok(())
-}

src/mcp/mod.rs

@@ -1,3 +1,5 @@
-// src/mcp/mod.rs
+pub mod base;
-pub mod server;
+pub mod extended;
-pub mod memory;
+
+pub use base::BaseMCPServer;
+pub use extended::ExtendedMCPServer;

src/mcp/server.rs

@@ -1,147 +0,0 @@
-// src/mcp/server.rs
-use crate::config::ConfigPaths;
-//use std::fs;
-use std::process::Command as OtherCommand;
-use std::env;
-use fs_extra::dir::{copy, CopyOptions};
-
-pub fn setup() {
-    println!("🔧 MCP Server環境をセットアップしています...");
-    let config = ConfigPaths::new();
-    let mcp_dir = config.mcp_dir();
-
-    // プロジェクトのmcp/ディレクトリからファイルをコピー
-    let current_dir = env::current_dir().expect("現在のディレクトリを取得できません");
-    let project_mcp_dir = current_dir.join("mcp");
-    if !project_mcp_dir.exists() {
-        eprintln!("❌ プロジェクトのmcp/ディレクトリが見つかりません: {}", project_mcp_dir.display());
-        return;
-    }
-
-    if mcp_dir.exists() {
-        fs_extra::dir::remove(&mcp_dir).expect("既存のmcp_dirの削除に失敗しました");
-    }
-
-    let mut options = CopyOptions::new();
-    options.overwrite = true; // 上書き
-    options.copy_inside = true; // 中身だけコピー
-
-    copy(&project_mcp_dir, &mcp_dir, &options).expect("コピーに失敗しました");   
-
-    // 仮想環境の作成
-    let venv_path = config.venv_path();
-    if !venv_path.exists() {
-        println!("🐍 仮想環境を作成しています...");
-        let output = OtherCommand::new("python3")
-            .args(&["-m", "venv", ".venv"])
-            .current_dir(&mcp_dir)
-            .output()
-            .expect("venvの作成に失敗しました");
-
-        if !output.status.success() {
-            eprintln!("❌ venv作成エラー: {}", String::from_utf8_lossy(&output.stderr));
-            return;
-        }
-        println!("✅ 仮想環境を作成しました");
-    } else {
-        println!("✅ 仮想環境は既に存在します");
-    }
-
-    // 依存関係のインストール
-    println!("📦 依存関係をインストールしています...");
-    let pip_path = config.pip_executable();
-    let output = OtherCommand::new(&pip_path)
-        .args(&["install", "-r", "requirements.txt"])
-        .current_dir(&mcp_dir)
-        .output()
-        .expect("pipコマンドの実行に失敗しました");
-
-    if !output.status.success() {
-        eprintln!("❌ pip installエラー: {}", String::from_utf8_lossy(&output.stderr));
-        return;
-    }
-
-    println!("✅ MCP Server環境のセットアップが完了しました!");
-    println!("📍 セットアップ場所: {}", mcp_dir.display());
-}
-
-pub async fn run() {
-    println!("🚀 MCP Serverを起動しています...");
-    
-    let config = ConfigPaths::new();
-    let mcp_dir = config.mcp_dir();
-    let python_path = config.python_executable();
-    let server_py_path = mcp_dir.join("server.py");
-
-    // セットアップの確認
-    if !server_py_path.exists() {
-        eprintln!("❌ server.pyが見つかりません。先に 'aigpt server setup' を実行してください。");
-        return;
-    }
-
-    if !python_path.exists() {
-        eprintln!("❌ Python実行ファイルが見つかりません。先に 'aigpt server setup' を実行してください。");
-        return;
-    }
-
-    // サーバーの起動
-    println!("🔗 サーバーを起動中... (Ctrl+Cで停止)");
-    let mut child = OtherCommand::new(&python_path)
-        .arg("server.py")
-        .current_dir(&mcp_dir)
-        .spawn()
-        .expect("MCP Serverの起動に失敗しました");
-
-    // サーバーの終了を待機
-    match child.wait() {
-        Ok(status) => {
-            if status.success() {
-                println!("✅ MCP Serverが正常に終了しました");
-            } else {
-                println!("❌ MCP Serverが異常終了しました: {}", status);
-            }
-        }
-        Err(e) => {
-            eprintln!("❌ MCP Serverの実行中にエラーが発生しました: {}", e);
-        }
-    }
-}
-
-pub async fn chat(message: &str) {
-    println!("💬 チャットを開始しています...");
-    
-    let config = ConfigPaths::new();
-    let mcp_dir = config.mcp_dir();
-    let python_path = config.python_executable();
-    let chat_py_path = mcp_dir.join("chat.py");
-
-    // セットアップの確認
-    if !chat_py_path.exists() {
-        eprintln!("❌ chat.pyが見つかりません。先に 'aigpt server setup' を実行してください。");
-        return;
-    }
-
-    if !python_path.exists() {
-        eprintln!("❌ Python実行ファイルが見つかりません。先に 'aigpt server setup' を実行してください。");
-        return;
-    }
-
-    // チャットの実行
-    let output = OtherCommand::new(&python_path)
-        .args(&["chat.py", message])
-        .current_dir(&mcp_dir)
-        .output()
-        .expect("chat.pyの実行に失敗しました");
-
-    if output.status.success() {
-        let stdout = String::from_utf8_lossy(&output.stdout);
-        let stderr = String::from_utf8_lossy(&output.stderr);
-        
-        if !stderr.is_empty() {
-            print!("{}", stderr);
-        }
-        print!("{}", stdout);
-    } else {
-        eprintln!("❌ チャット実行エラー: {}", String::from_utf8_lossy(&output.stderr));
-    }
-}

src/memory.rs

@@ -0,0 +1,241 @@
+use anyhow::{Context, Result};
+use chrono::{DateTime, Utc};
+use serde::{Deserialize, Serialize};
+use std::collections::HashMap;
+use std::path::PathBuf;
+use uuid::Uuid;
+
+#[derive(Debug, Clone, Serialize, Deserialize)]
+pub struct Memory {
+    pub id: String,
+    pub content: String,
+    pub created_at: DateTime<Utc>,
+    pub updated_at: DateTime<Utc>,
+}
+
+#[derive(Debug, Clone, Serialize, Deserialize)]
+pub struct Conversation {
+    pub id: String,
+    pub title: String,
+    pub created_at: DateTime<Utc>,
+    pub message_count: u32,
+}
+
+#[derive(Debug, Clone, Serialize, Deserialize)]
+struct ChatGPTNode {
+    id: String,
+    children: Vec<String>,
+    parent: Option<String>,
+    message: Option<ChatGPTMessage>,
+}
+
+#[derive(Debug, Clone, Serialize, Deserialize)]
+struct ChatGPTMessage {
+    id: String,
+    author: ChatGPTAuthor,
+    content: ChatGPTContent,
+    create_time: Option<f64>,
+}
+
+#[derive(Debug, Clone, Serialize, Deserialize)]
+struct ChatGPTAuthor {
+    role: String,
+}
+
+#[derive(Debug, Clone, Serialize, Deserialize)]
+#[serde(untagged)]
+enum ChatGPTContent {
+    Text {
+        content_type: String,
+        parts: Vec<String>,
+    },
+    Other(serde_json::Value),
+}
+
+#[derive(Debug, Clone, Serialize, Deserialize)]
+struct ChatGPTConversation {
+    #[serde(default)]
+    id: String,
+    #[serde(alias = "conversation_id")]
+    conversation_id: Option<String>,
+    title: String,
+    create_time: f64,
+    mapping: HashMap<String, ChatGPTNode>,
+}
+
+pub struct MemoryManager {
+    memories: HashMap<String, Memory>,
+    conversations: HashMap<String, Conversation>,
+    data_file: PathBuf,
+}
+
+impl MemoryManager {
+    pub async fn new() -> Result<Self> {
+        let data_dir = dirs::config_dir()
+            .context("Could not find config directory")?
+            .join("syui")
+            .join("ai")
+            .join("gpt");
+        
+        std::fs::create_dir_all(&data_dir)?;
+        
+        let data_file = data_dir.join("memory.json");
+        
+        let (memories, conversations) = if data_file.exists() {
+            Self::load_data(&data_file)?
+        } else {
+            (HashMap::new(), HashMap::new())
+        };
+
+        Ok(MemoryManager {
+            memories,
+            conversations,
+            data_file,
+        })
+    }
+
+    pub fn create_memory(&mut self, content: &str) -> Result<String> {
+        let id = Uuid::new_v4().to_string();
+        let now = Utc::now();
+        
+        let memory = Memory {
+            id: id.clone(),
+            content: content.to_string(),
+            created_at: now,
+            updated_at: now,
+        };
+        
+        self.memories.insert(id.clone(), memory);
+        self.save_data()?;
+        
+        Ok(id)
+    }
+
+    pub fn update_memory(&mut self, id: &str, content: &str) -> Result<()> {
+        if let Some(memory) = self.memories.get_mut(id) {
+            memory.content = content.to_string();
+            memory.updated_at = Utc::now();
+            self.save_data()?;
+            Ok(())
+        } else {
+            Err(anyhow::anyhow!("Memory not found: {}", id))
+        }
+    }
+
+    pub fn delete_memory(&mut self, id: &str) -> Result<()> {
+        if self.memories.remove(id).is_some() {
+            self.save_data()?;
+            Ok(())
+        } else {
+            Err(anyhow::anyhow!("Memory not found: {}", id))
+        }
+    }
+
+    pub fn search_memories(&self, query: &str) -> Vec<&Memory> {
+        let query_lower = query.to_lowercase();
+        let mut results: Vec<_> = self.memories
+            .values()
+            .filter(|memory| memory.content.to_lowercase().contains(&query_lower))
+            .collect();
+        
+        results.sort_by(|a, b| b.updated_at.cmp(&a.updated_at));
+        results
+    }
+
+    pub fn list_conversations(&self) -> Vec<&Conversation> {
+        let mut conversations: Vec<_> = self.conversations.values().collect();
+        conversations.sort_by(|a, b| b.created_at.cmp(&a.created_at));
+        conversations
+    }
+
+    #[allow(dead_code)]
+    pub async fn import_chatgpt_conversations(&mut self, file_path: &PathBuf) -> Result<()> {
+        let content = std::fs::read_to_string(file_path)
+            .context("Failed to read conversations file")?;
+        
+        let chatgpt_conversations: Vec<ChatGPTConversation> = serde_json::from_str(&content)
+            .context("Failed to parse ChatGPT conversations")?;
+
+        let mut imported_memories = 0;
+        let mut imported_conversations = 0;
+
+        for conv in chatgpt_conversations {
+            // Get the actual conversation ID
+            let conv_id = if !conv.id.is_empty() {
+                conv.id.clone()
+            } else if let Some(cid) = conv.conversation_id {
+                cid
+            } else {
+                Uuid::new_v4().to_string()
+            };
+            
+            // Add conversation
+            let conversation = Conversation {
+                id: conv_id.clone(),
+                title: conv.title.clone(),
+                created_at: DateTime::from_timestamp(conv.create_time as i64, 0)
+                    .unwrap_or_else(Utc::now),
+                message_count: conv.mapping.len() as u32,
+            };
+            self.conversations.insert(conv_id.clone(), conversation);
+            imported_conversations += 1;
+
+            // Extract memories from messages
+            for (_, node) in conv.mapping {
+                if let Some(message) = node.message {
+                    if let ChatGPTContent::Text { parts, .. } = message.content {
+                        for part in parts {
+                            if !part.trim().is_empty() && part.len() > 10 {
+                                let memory_content = format!("[{}] {}", conv.title, part);
+                                self.create_memory(&memory_content)?;
+                                imported_memories += 1;
+                            }
+                        }
+                    }
+                }
+            }
+        }
+
+        println!("Imported {} conversations and {} memories", 
+                imported_conversations, imported_memories);
+        
+        Ok(())
+    }
+
+    fn load_data(file_path: &PathBuf) -> Result<(HashMap<String, Memory>, HashMap<String, Conversation>)> {
+        let content = std::fs::read_to_string(file_path)
+            .context("Failed to read data file")?;
+        
+        #[derive(Deserialize)]
+        struct Data {
+            memories: HashMap<String, Memory>,
+            conversations: HashMap<String, Conversation>,
+        }
+        
+        let data: Data = serde_json::from_str(&content)
+            .context("Failed to parse data file")?;
+        
+        Ok((data.memories, data.conversations))
+    }
+
+    fn save_data(&self) -> Result<()> {
+        #[derive(Serialize)]
+        struct Data<'a> {
+            memories: &'a HashMap<String, Memory>,
+            conversations: &'a HashMap<String, Conversation>,
+        }
+        
+        let data = Data {
+            memories: &self.memories,
+            conversations: &self.conversations,
+        };
+        
+        let content = serde_json::to_string_pretty(&data)
+            .context("Failed to serialize data")?;
+        
+        std::fs::write(&self.data_file, content)
+            .context("Failed to write data file")?;
+        
+        Ok(())
+    }
+}