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CrewAI

Use AllMCP tools in CrewAI agents via langchain-mcp-adapters.

Install

pip install crewai langchain-mcp-adapters langchain-anthropic

Minimal example

import asyncio
from crewai import Agent, Task, Crew
from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain_anthropic import ChatAnthropic


async def run_crm_crew():
    client = MultiServerMCPClient({
        "allmcp": {
            "url": "https://go.allmcp.co/mcp/",
            "transport": "streamable_http",
            "headers": {"X-API-Key": "YOUR_API_KEY"},
        }
    })
    tools = await client.get_tools()
    llm = ChatAnthropic(model="claude-sonnet-4-6")

    crm_agent = Agent(
        role="CRM Analyst",
        goal="Analyze sales pipeline and surface actionable insights",
        backstory="You are an expert sales analyst with deep CRM knowledge.",
        tools=tools,
        llm=llm,
        verbose=True,
    )

    task = Task(
        description=(
            "List all open deals in Bitrix24, group them by stage, "
            "and identify the top 3 deals most likely to close this week."
        ),
        expected_output="A ranked list of top 3 deals with reasoning.",
        agent=crm_agent,
    )

    crew = Crew(agents=[crm_agent], tasks=[task], verbose=True)
    result = crew.kickoff()
    return result


asyncio.run(run_crm_crew())

Multi-agent crew

async def run_sales_ops_crew():
    client = MultiServerMCPClient({
        "allmcp": {
            "url": "https://go.allmcp.co/mcp/",
            "transport": "streamable_http",
            "headers": {"X-API-Key": "YOUR_API_KEY"},
        }
    })
    tools = await client.get_tools()
    llm = ChatAnthropic(model="claude-sonnet-4-6")

    researcher = Agent(
        role="Sales Researcher",
        goal="Pull raw data from the CRM",
        tools=tools,
        llm=llm,
    )

    analyst = Agent(
        role="Sales Analyst",
        goal="Identify trends and insights from CRM data",
        llm=llm,
    )

    gather_task = Task(
        description="List all leads created in the last 7 days with their source and status.",
        expected_output="Raw list of leads with source and status fields.",
        agent=researcher,
    )

    analyze_task = Task(
        description="Based on the leads data, identify the top 2 lead sources by conversion rate.",
        expected_output="Top 2 lead sources with conversion rates.",
        agent=analyst,
        context=[gather_task],
    )

    crew = Crew(
        agents=[researcher, analyst],
        tasks=[gather_task, analyze_task],
    )
    return crew.kickoff()

Multi-user setup

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

Frameworks overview

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