连接到多个 MCP 服务器

概览

crewai-tools 中的 MCPServerAdapter 允许你同时连接到多个 MCP 服务器。当你的代理需要访问分布在不同服务或环境中的工具时，这很有用。适配器会聚合所有指定服务器的工具，并将它们提供给你的 CrewAI 代理。

配置

要连接到多个服务器，你需要向 MCPServerAdapter 提供一个服务器参数字典列表。列表中的每个字典都应定义一个 MCP 服务器的参数。

列表中每个服务器支持的传输类型包括 stdio、sse 和 streamable-http。

from crewai import Agent, Task, Crew, Process
from crewai_tools import MCPServerAdapter
from mcp import StdioServerParameters # Needed for Stdio example

# Define parameters for multiple MCP servers
server_params_list = [
    # Streamable HTTP Server
    {
        "url": "http://localhost:8001/mcp",
        "transport": "streamable-http"
    },
    # SSE Server
    {
        "url": "http://localhost:8000/sse",
        "transport": "sse"
    },
    # StdIO Server
    StdioServerParameters(
        command="python3",
        args=["servers/your_stdio_server.py"],
        env={"UV_PYTHON": "3.12", **os.environ},
    )
]

try:
    with MCPServerAdapter(server_params_list) as aggregated_tools:
        print(f"Available aggregated tools: {[tool.name for tool in aggregated_tools]}")

        multi_server_agent = Agent(
            role="Versatile Assistant",
            goal="Utilize tools from local Stdio, remote SSE, and remote HTTP MCP servers.",
            backstory="An AI agent capable of leveraging a diverse set of tools from multiple sources.",
            tools=aggregated_tools, # All tools are available here
            verbose=True,
        )

        ... # Your other agent, tasks, and crew code here

except Exception as e:
    print(f"Error connecting to or using multiple MCP servers (Managed): {e}")
    print("Ensure all MCP servers are running and accessible with correct configurations.")

连接管理

使用上下文管理器（with 语句）时，MCPServerAdapter 会负责配置好所有 MCP 服务器连接的生命周期（启动和停止）。这简化了资源管理，并确保在上下文退出时所有连接都被正确关闭。