How to integrate Composio MCP with CrewAI

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Introduction

This guide walks you through connecting Composio to CrewAI using the Composio tool router. By the end, you'll have a working Composio agent that can generate a step-by-step workflow plan, check active connections for all toolkits, download public s3 file to local path, show tool dependencies for workflow setup through natural language commands.

This guide will help you understand how to give your CrewAI agent real control over a Composio account through Composio's Composio MCP server.

Before we dive in, let's take a quick look at the key ideas and tools involved.

TL;DR

Here's what you'll learn:
  • Get a Composio API key and configure your Composio connection
  • Set up CrewAI with an MCP enabled agent
  • Create a Tool Router session or standalone MCP server for Composio
  • Build a conversational loop where your agent can execute Composio operations

What is CrewAI?

CrewAI is a powerful framework for building multi-agent AI systems. It provides primitives for defining agents with specific roles, creating tasks, and orchestrating workflows through crews.

Key features include:

  • Agent Roles: Define specialized agents with specific goals and backstories
  • Task Management: Create tasks with clear descriptions and expected outputs
  • Crew Orchestration: Combine agents and tasks into collaborative workflows
  • MCP Integration: Connect to external tools through Model Context Protocol

What is the Composio MCP server, and what's possible with it?

The Composio MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Composio account. It provides structured and secure access to your connected tools, so your agent can plan workflows, orchestrate complex actions, manage integrations, and execute cross-tool automations on your behalf.

  • Automated workflow planning and execution: The agent can generate and run step-by-step plans for complex, multi-tool use cases—ensuring tasks are completed reliably, even when they span multiple services.
  • Connection management and discovery: Effortlessly check the status of multiple toolkit connections, discover what integrations are active, and manage how your agent connects to different services.
  • Tool and dependency exploration: Ask your agent to map out tool dependencies, discover related tools, and understand which tools work best together for your workflow.
  • Direct code and command execution: Let the agent run code snippets or shell commands in supported environments, tying together automation across your stack.
  • Bulk and parallel operations: Use specialized tools for parallel execution or to handle many similar tasks at once—speeding up large automations by making multiple calls in a single workflow.

Supported Tools & Triggers

Tools
Ask OracleStatic helper that returns a comprehensive system prompt describing how to plan and execute tasks using the available composio tools and workflows.
Check active connection (deprecated)Deprecated: use check active connections instead for bulk operations.
Check multiple active connectionsCheck active connection status for multiple toolkits or specific connected account ids.
Create PlanThis is a workflow builder that ensures the LLM produces a complete, step-by-step plan for any use case.
Download S3 FileDownload a file from a public s3 (or r2) url to a local path.
Enable triggerEnable a specific trigger for the authenticated user.
Execute agentExecute complex workflows using ai agent reasoning between multiple tool calls.
Execute Composio ToolExecute a tool using the composio api.
Get Tool Dependency GraphGet the dependency graph for a given tool, showing related parent tools that might be useful.
Get required parameters for connectionGets the required parameters for connecting to a toolkit via initiate connection.
Get response schemaRetrieves the response schema for a specified composio tool.
Initiate connectionInitiate a connection to a toolkit with comprehensive authentication support.
List toolkitsList all the available toolkits on composio with filtering options.
List triggersList available triggers and their configuration schemas.
Manage connectionManage a connection to a toolkit with comprehensive authentication support.
Manage connectionsCreate or manage connections to user's apps.
Multi Execute Composio ToolsFast and parallel tool executor for tools discovered through COMPOSIO_SEARCH_TOOLS.
Run bash commandsExecute bash commands in a REMOTE sandbox for file operations, data processing, and system tasks.
Execute Code remotely in work benchProcess REMOTE FILES or script BULK TOOL EXECUTIONS using Python code IN A REMOTE SANDBOX.
Retrieve ToolkitsToolkits are like github, linear, gmail, etc.
Search agentDiscover tools and analyze dependencies for complex workflows using ai agent.
Search Composio ToolsMCP Server Info: COMPOSIO MCP connects 500+ apps—Slack, GitHub, Notion, Google Workspace (Gmail, Sheets, Drive, Calendar), Microsoft (Outlook, Teams), X, Figma, Web Search, Meta apps (WhatsApp, Instagram), TikTok, AI tools like Nano Banana & Veo3, and more—for seamless cross-app automation.
Wait for connectionWait for the user to complete authentication AFTER you have given them an auth URL from COMPOSIO_MANAGE_CONNECTIONS.
Create / Update Recipe from WorkflowConvert the executed workflow into a notebook.
Execute RecipeExecutes a Recipe
Create / Update Skill from WorkflowConvert the executed workflow into a skill using Python Pydantic code.
Get Existing Recipe DetailsGet the details of the existing recipe for a given recipe id.

What is the Composio tool router, and how does it fit here?

What is Tool Router?

Composio's Tool Router helps agents find the right tools for a task at runtime. You can plug in multiple toolkits (like Gmail, HubSpot, and GitHub), and the agent will identify the relevant app and action to complete multi-step workflows. This can reduce token usage and improve the reliability of tool calls. Read more here: Getting started with Tool Router

The tool router generates a secure MCP URL that your agents can access to perform actions.

How the Tool Router works

The Tool Router follows a three-phase workflow:

  1. Discovery: Searches for tools matching your task and returns relevant toolkits with their details.
  2. Authentication: Checks for active connections. If missing, creates an auth config and returns a connection URL via Auth Link.
  3. Execution: Executes the action using the authenticated connection.

Step-by-step Guide

Prerequisites

Before starting, make sure you have:
  • Python 3.9 or higher
  • A Composio account and API key
  • A Composio connection authorized in Composio
  • An OpenAI API key for the CrewAI LLM
  • Basic familiarity with Python

Getting API Keys for OpenAI and Composio

OpenAI API Key
  • Go to the OpenAI dashboard and create an API key. You'll need credits to use the models, or you can connect to another model provider.
  • Keep the API key safe.
Composio API Key
  • Log in to the Composio dashboard.
  • Navigate to your API settings and generate a new API key.
  • Store this key securely as you'll need it for authentication.

Install dependencies

bash
pip install composio crewai crewai-tools python-dotenv
What's happening:
  • composio connects your agent to Composio via MCP
  • crewai provides Agent, Task, Crew, and LLM primitives
  • crewai-tools includes MCP helpers
  • python-dotenv loads environment variables from .env

Set up environment variables

bash
COMPOSIO_API_KEY=your_composio_api_key_here
USER_ID=your_user_id_here
OPENAI_API_KEY=your_openai_api_key_here

Create a .env file in your project root.

What's happening:

  • COMPOSIO_API_KEY authenticates with Composio
  • USER_ID scopes the session to your account
  • OPENAI_API_KEY lets CrewAI use your chosen OpenAI model

Import dependencies

python
from crewai import Agent, Task, Crew, LLM
from crewai_tools import MCPServerAdapter  # optional import if you plan to adapt tools
from composio import Composio
from dotenv import load_dotenv
import os
from crewai.mcp import MCPServerHTTP

load_dotenv()
What's happening:
  • CrewAI classes define agents and tasks, and run the workflow
  • MCPServerHTTP connects the agent to an MCP endpoint
  • Composio will give you a short lived Composio MCP URL

Create a Composio Tool Router session for Composio

python
composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
session = composio.create(
    user_id=os.getenv("USER_ID"),
    toolkits=["composio"],
)
url = session.mcp.url
What's happening:
  • You create a Composio only session through Composio
  • Composio returns an MCP HTTP URL that exposes Composio tools

Configure the LLM

python
llm = LLM(
    model="gpt-5-mini",
    api_key=os.getenv("OPENAI_API_KEY"),
)
What's happening:
  • CrewAI will call this LLM for planning and responses
  • You can swap in a different model if needed

Attach the MCP server and create the agent

python
toolkit_agent = Agent(
    role="Composio Assistant",
    goal="Help users interact with Composio through natural language commands",
    backstory=(
        "You are an expert assistant with access to Composio tools. "
        "You can perform various Composio operations on behalf of the user."
    ),
    mcps=[
        MCPServerHTTP(
            url=url,
            streamable=True,
            cache_tools_list=True,
            headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")},
        ),
    ],
    llm=llm,
    verbose=True,
    max_iter=10,
)
What's happening:
  • MCPServerHTTP connects the agent to the Composio MCP endpoint
  • cache_tools_list saves a tools catalog for faster subsequent runs
  • verbose helps you see what the agent is doing

Add a REPL loop with Task and Crew

python
print("Chat started! Type 'exit' or 'quit' to end.\n")
print("Try asking the agent to perform Composio operations.\n")

conversation_context = ""

while True:
    user_input = input("You: ").strip()

    if user_input.lower() in ["exit", "quit", "bye"]:
        print("\nGoodbye!")
        break

    if not user_input:
        continue

    conversation_context += f"\nUser: {user_input}\n"
    print("\nAgent is thinking...\n")

    task = Task(
        description=(
            f"Based on the conversation history:\n{conversation_context}\n\n"
            f"Current user request: {user_input}\n\n"
            f"Please help the user with their Composio related request."
        ),
        expected_output="A helpful response addressing the user's request",
        agent=toolkit_agent,
    )

    crew = Crew(
        agents=[toolkit_agent],
        tasks=[task],
        verbose=False,
    )

    result = crew.kickoff()
    response = str(result)

    conversation_context += f"Agent: {response}\n"
    print(f"Agent: {response}\n")
What's happening:
  • You build a simple chat loop and keep a running context
  • Each user turn becomes a Task handled by the same agent
  • Crew executes the task and returns a response

Run the application

python
if __name__ == "__main__":
    main()
What's happening:
  • Standard Python entry point so you can run python crewai_composio_agent.py

Complete Code

Here's the complete code to get you started with Composio and CrewAI:

python
# file: crewai_composio_agent.py
from crewai import Agent, Task, Crew, LLM
from crewai_tools import MCPServerAdapter  # optional
from composio import Composio
from dotenv import load_dotenv
import os
from crewai.mcp import MCPServerHTTP

load_dotenv()

def main():
    # Initialize Composio and create a Composio session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["composio"],
    )
    url = session.mcp.url

    # Configure LLM
    llm = LLM(
        model="gpt-5-mini",
        api_key=os.getenv("OPENAI_API_KEY"),
    )

    # Create Composio assistant agent
    toolkit_agent = Agent(
        role="Composio Assistant",
        goal="Help users interact with Composio through natural language commands",
        backstory=(
            "You are an expert assistant with access to Composio tools. "
            "You can perform various Composio operations on behalf of the user."
        ),
        mcps=[
            MCPServerHTTP(
                url=url,
                streamable=True,
                cache_tools_list=True,
                headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")},
            ),
        ],
        llm=llm,
        verbose=True,
        max_iter=10,
    )

    print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
    print("Try asking the agent to perform Composio operations.\n")

    conversation_context = ""

    while True:
        user_input = input("You: ").strip()

        if user_input.lower() in ["exit", "quit", "bye"]:
            print("\nGoodbye!")
            break

        if not user_input:
            continue

        conversation_context += f"\nUser: {user_input}\n"
        print("\nAgent is thinking...\n")

        task = Task(
            description=(
                f"Based on the conversation history:\n{conversation_context}\n\n"
                f"Current user request: {user_input}\n\n"
                f"Please help the user with their Composio related request."
            ),
            expected_output="A helpful response addressing the user's request",
            agent=toolkit_agent,
        )

        crew = Crew(
            agents=[toolkit_agent],
            tasks=[task],
            verbose=False,
        )

        result = crew.kickoff()
        response = str(result)

        conversation_context += f"Agent: {response}\n"
        print(f"Agent: {response}\n")

if __name__ == "__main__":
    main()

Conclusion

You now have a CrewAI agent connected to Composio through Composio's Tool Router. The agent can perform Composio operations through natural language commands. Next steps:
  • Add role-specific instructions to customize agent behavior
  • Plug in more toolkits for multi-app workflows
  • Chain tasks for complex multi-step operations

How to build Composio MCP Agent with another framework

OpenAI Agents SDK

OpenAI Agents SDK

Use Composio MCP with OpenAI Agents SDK

Claude Agent SDK

Claude Agent SDK

Use Composio MCP with Claude Agent SDK

Google ADK

Google ADK

Use Composio MCP with Google ADK

LangChain

LangChain

Use Composio MCP with LangChain

Vercel AI SDK

Vercel AI SDK

Use Composio MCP with Vercel AI SDK

Mastra AI

Mastra AI

Use Composio MCP with Mastra AI

LlamaIndex

LlamaIndex

Use Composio MCP with LlamaIndex

FAQ

What are the differences in Tool Router MCP and Composio MCP?

With a standalone Composio MCP server, the agents and LLMs can only access a fixed set of Composio tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Composio and many other apps based on the task at hand, all through a single MCP endpoint.

Can I use Tool Router MCP with CrewAI?

Yes, you can. CrewAI fully supports MCP integration. You get structured tool calling, message history handling, and model orchestration while Tool Router takes care of discovering and serving the right Composio tools.

Can I manage the permissions and scopes for Composio while using Tool Router?

Yes, absolutely. You can configure which Composio scopes and actions are allowed when connecting your account to Composio. You can also bring your own OAuth credentials or API configuration so you keep full control over what the agent can do.

How safe is my data with Composio Tool Router?

All sensitive data such as tokens, keys, and configuration is fully encrypted at rest and in transit. Composio is SOC 2 Type 2 compliant and follows strict security practices so your Composio data and credentials are handled as safely as possible.

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Context
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