MCP-сервер для управления памятью агента: server.py

server.py

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+import json
+import uuid
+from typing import List, Optional
+
+from fastapi import FastAPI, HTTPException, Request
+from fastapi.responses import JSONResponse
+from fastapi.middleware.cors import CORSMiddleware
+from fastapi.logger import logger as fastapi_logger
+
+from fastmcp import MCPServer, MCPRequest, MCPResponse
+from langchain.embeddings import OpenAIEmbeddings
+from langchain.vectorstores import Qdrant
+from langchain.schema import Document
+
+from rich.console import Console
+from rich.table import Table
+
+# Настройки сервера
+APP_NAME = "AgentMemoryMCP"
+APP_VERSION = "1.0.0"
+QDRANT_URL = "http://localhost:6333"
+COLLECTION_NAME = "agent_memory"
+
+# Инициализация консоли rich
+console = Console()
+
+# Создаём FastAPI приложение
+app = FastAPI(title=APP_NAME, version=APP_VERSION)
+
+# CORS (если понадобится)
+app.add_middleware(
+    CORSMiddleware,
+    allow_origins=["*"],
+    allow_credentials=True,
+    allow_methods=["*"],
+    allow_headers=["*"],
+)
+
+# Инициализация Qdrant
+embeddings = OpenAIEmbeddings()
+vectorstore = Qdrant(
+    client=qdrant_client := Qdrant(
+        url=QDRANT_URL,
+        collection_name=COLLECTION_NAME,
+        embeddings=embeddings,
+    ),
+    embeddings=embeddings,
+    collection_name=COLLECTION_NAME,
+)
+
+# Создаём MCP сервер
+mcp_server = MCPServer(app=app, name=APP_NAME, version=APP_VERSION)
+
+
+# Вспомогательные функции
+def _log_request(req: MCPRequest):
+    table = Table(title="MCP Request", show_header=True, header_style="bold magenta")
+    table.add_column("Method")
+    table.add_column("Path")
+    table.add_column("Body")
+    table.add_row(req.method, req.path, json.dumps(req.body, indent=2))
+    console.print(table)
+
+
+def _log_response(res: MCPResponse):
+    table = Table(title="MCP Response", show_header=True, header_style="bold green")
+    table.add_column("Status")
+    table.add_column("Body")
+    table.add_row(str(res.status), json.dumps(res.body, indent=2))
+    console.print(table)
+
+
+# Обработчики MCP
+@mcp_server.on("memory.add")
+async def handle_memory_add(req: MCPRequest) -> MCPResponse:
+    _log_request(req)
+    content = req.body.get("content")
+    if not content:
+        raise HTTPException(status_code=400, detail="Missing 'content' field")
+    # Создаём документ и сохраняем в Qdrant
+    doc = Document(page_content=content, metadata={"id": str(uuid.uuid4())})
+    vectorstore.add_documents([doc])
+    res = MCPResponse(status=200, body={"id": doc.metadata["id"]})
+    _log_response(res)
+    return res
+
+
+@mcp_server.on("memory.get")
+async def handle_memory_get(req: MCPRequest) -> MCPResponse:
+    _log_request(req)
+    query = req.body.get("query")
+    if not query:
+        raise HTTPException(status_code=400, detail="Missing 'query' field")
+    # Поиск похожих документов
+    results = vectorstore.similarity_search(query, k=5)
+    res_body = [
+        {"id": doc.metadata.get("id"), "content": doc.page_content} for doc in results
+    ]
+    res = MCPResponse(status=200, body=res_body)
+    _log_response(res)
+    return res
+
+
+@mcp_server.on("memory.delete")
+async def handle_memory_delete(req: MCPRequest) -> MCPResponse:
+    _log_request(req)
+    doc_id = req.body.get("id")
+    if not doc_id:
+        raise HTTPException(status_code=400, detail="Missing 'id' field")
+    # Удаляем документ по id
+    deleted = vectorstore.delete(ids=[doc_id])
+    res = MCPResponse(status=200, body={"deleted": deleted})
+    _log_response(res)
+    return res
+
+
+# Запуск через uvicorn
+if __name__ == "__main__":
+    import uvicorn
+
+    uvicorn.run(app, host="0.0.0.0", port=8000)