AutoGen

Use AllMCP tools in Microsoft AutoGen agents via autogen-ext[mcp].

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Install

install

pip install 'autogen-ext[mcp]' 'autogen-ext[anthropic]' autogen-agentchat

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Minimal example

agent.py

import asyncio
from autogen_ext.tools.mcp import StreamableHttpServerParams, mcp_server_tools
from autogen_agentchat.agents import AssistantAgent
from autogen_agentchat.ui import Console
from autogen_ext.models.anthropic import AnthropicChatCompletionClient


async def main():
    params = StreamableHttpServerParams(
        url="https://go.allmcp.co/mcp/",
        headers={"X-API-Key": "YOUR_API_KEY"},
    )
    tools = await mcp_server_tools(params)

    agent = AssistantAgent(
        name="crm_agent",
        model_client=AnthropicChatCompletionClient(model="claude-sonnet-4-6"),
        tools=tools,
        system_message="You are a CRM assistant. Use AllMCP tools to manage the user's data.",
    )

    await Console(agent.run_stream(task="List the top 5 contacts in my CRM"))


asyncio.run(main())

Note

AutoGen is async. mcp_server_tools and the agent’s run_stream are awaited inside an async def main(), launched with asyncio.run(main()).

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Multi-agent setup

multi_agent.py

import asyncio
from autogen_agentchat.agents import AssistantAgent
from autogen_agentchat.teams import RoundRobinGroupChat
from autogen_agentchat.ui import Console
from autogen_ext.tools.mcp import StreamableHttpServerParams, mcp_server_tools
from autogen_ext.models.anthropic import AnthropicChatCompletionClient


async def main():
    params = StreamableHttpServerParams(
        url="https://go.allmcp.co/mcp/",
        headers={"X-API-Key": "YOUR_API_KEY"},
    )
    tools = await mcp_server_tools(params)
    model = AnthropicChatCompletionClient(model="claude-sonnet-4-6")

    data_agent = AssistantAgent(
        name="DataFetcher",
        model_client=model,
        tools=tools,
        system_message="Fetch raw data from the CRM. Do not analyze — just retrieve.",
    )

    analyst_agent = AssistantAgent(
        name="Analyst",
        model_client=model,
        system_message="Analyze data provided by DataFetcher and produce insights.",
    )

    team = RoundRobinGroupChat([data_agent, analyst_agent], max_turns=4)
    await Console(team.run_stream(task="Summarize this week's new leads by source"))


asyncio.run(main())

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Multi-user setup

multi_user.py

def make_params(user_id: str) -> StreamableHttpServerParams:
    return StreamableHttpServerParams(
        url=f"https://go.allmcp.co/mcp/?user_id={user_id}",
        headers={"X-API-Key": "YOUR_API_KEY"},
    )

async def run_for_user(user_id: str, task: str):
    params = make_params(user_id)
    tools = await mcp_server_tools(params)
    agent = AssistantAgent(
        name="agent",
        model_client=AnthropicChatCompletionClient(model="claude-sonnet-4-6"),
        tools=tools,
    )
    await Console(agent.run_stream(task=task))

Note

Scope tools to a user. Append ?user_id={user_id} to the endpoint URL to route each agent run to that user’s connected providers and credentials.

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See also

Frameworks overview

Browse providers See every provider you can connect and the tools each one offers.