MCP实现Agentic RAG server案例

使用dify的知识库 api，fastapi创建mcp server

代码

@mcp.tool()
async def rag_retrieve(query: str) -> dict:
    """
    Name:
        ***产品业务服务等相关客服问答知识检索服务

    Description:
        提供****业务服务等相关客服问答知识检索服务，根据输入query返回结果。
    
    Args:
        query: 搜索的内容，参数必传，例如 'query=客服电话'
    """
    url = "http://117.-dbb9-4cb9-a172-482c6571aab8/retrieve"
    token = "dataset-VVqUSZNMzMrVLiB4wQbvlYCW"  # 你的token

    headers = {
        "Authorization": f"Bearer {token}",
        # 使用 json= 参数时会自动设置 Content-Type，此处保留以匹配原始请求
        "Content-Type": "application/json"
    }

    payload = {
        "query": query,
        "retrieval_model": {
            "search_method": "semantic_search",
            "reranking_enable": False,  # false → False
            "reranking_mode": None,  # null → None
            "reranking_model": {
                "reranking_provider_name": "",
                "reranking_model_name": ""
            },
            "weights": None,  # null → None
            "top_k": 2,
            "score_threshold_enabled": False,  # false → False
            "score_threshold": None,  # null → None
            
        }
    }
    logging.info(f"rag_retrieve query:{query}")
    # ✅ 使用全局连接池
    client = await get_http_client()
    
    try:
        response = await client.post(url, headers=headers, json=payload)
        response.raise_for_status()
        result = response.json()
        logging.info(f"🔍 rag_retrieve 完成")
        return result
    except Exception as e:
        logging.error(f"❌ rag_retrieve 失败: {e}")
        raise ValueError(f"调用API失败: {e}")

cherry studio客服端访问