# server.py
#from fastapi import FastAPI
#from fastapi_mcp import FastApiMCP
#
#app = FastAPI()
#
#@app.get("/items/{item_id}", operation_id="get_item")
#async def read_item(item_id: int):
#    return {"item_id": item_id, "name": f"Item {item_id}"}
#
## MCPサーバを作成し、FastAPIアプリにマウント
#mcp = FastApiMCP(
#    app,
#    name="My API MCP",
#    description="My API description"
#)
#mcp.mount()
#
#if __name__ == "__main__":
#    import uvicorn
#    uvicorn.run(app, host="0.0.0.0", port=8000)

from fastapi import FastAPI
from fastapi_mcp import FastApiMCP
from pydantic import BaseModel
from memory_store import save_message, load_messages

app = FastAPI()
mcp = FastApiMCP(app, name="aigpt-agent", description="MCP Server for AI memory")

# --- モデル定義 ---
class ChatInput(BaseModel):
    message: str

class MemoryInput(BaseModel):
    sender: str
    message: str

# --- ツール（エンドポイント）定義 ---
@app.post("/chat", operation_id="chat")
async def chat(input: ChatInput):
    save_message("user", input.message)
    response = f"AI: 「{input.message}」を受け取りました！"
    save_message("ai", response)
    return {"response": response}

@app.post("/memory", operation_id="save_memory")
async def memory_post(input: MemoryInput):
    save_message(input.sender, input.message)
    return {"status": "saved"}

@app.get("/memory", operation_id="get_memory")
async def memory_get():
    return {"messages": load_messages()}

# --- MCP 初期化 ---
mcp.mount()

if __name__ == "__main__":
    import uvicorn
    print("🚀 Starting MCP server...")
    uvicorn.run(app, host="127.0.0.1", port=5000)