How to integrate Google Meet MCP with CrewAI

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Introduction

This guide walks you through connecting Google Meet to CrewAI using the Composio tool router. By the end, you'll have a working Google Meet agent that can schedule a new video meeting for tomorrow, list all meetings i hosted last week, get transcript from my most recent meeting, update access settings for a specific meet through natural language commands.

This guide will help you understand how to give your CrewAI agent real control over a Google Meet account through Composio's Google Meet 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 Google Meet connection
  • Set up CrewAI with an MCP enabled agent
  • Create a Tool Router session or standalone MCP server for Google Meet
  • Build a conversational loop where your agent can execute Google Meet 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 Google Meet MCP server, and what's possible with it?

The Google Meet MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Google Meet account. It provides structured and secure access to your meetings and recordings, so your agent can schedule new meetings, fetch past conference details, access recordings and transcripts, and manage meeting spaces on your behalf.

  • Instant meeting scheduling and management: Ask your agent to create new Google Meet sessions or update existing meeting spaces with specific settings and access controls.
  • Comprehensive meeting record retrieval: Have your agent list all past conference records, filter them by time or criteria, and pull up detailed information about any meeting.
  • Access recordings and transcripts: Effortlessly retrieve recordings or full transcripts of your previous Google Meet conferences for reference, review, or sharing.
  • Participant session insights: Let your agent list all participants in a given meeting or fetch detailed information about specific attendee sessions for attendance tracking or follow-up.
  • Flexible post-meeting actions: Enable your agent to update meeting spaces, manage access, and ensure your Google Meet environment stays organized and up to date.

Supported Tools & Triggers

Tools
Create a MeetCreates a new google meet space, optionally configuring its access type and entry point access controls.
Get conference recordGet conference record
Get Meet detailsRetrieve details of a google meet space using its unique identifier.
Get Participant SessionTool to get a specific participant session from a conference record.
Get recordings by conference record IDRetrieves recordings from google meet for a given conference record id.
Get transcripts by conference record IDRetrieves all transcripts for a specific google meet conference using its conferencerecord id.
List Conference RecordsTool to list conference records.
List Participant SessionsTool to list all participant sessions for a specific conference record in google meet.
Update Google Meet SpaceUpdates a meeting space.

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 Google Meet 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 Google Meet 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 Google Meet MCP URL

Create a Composio Tool Router session for Google Meet

python
composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
session = composio.create(
    user_id=os.getenv("USER_ID"),
    toolkits=["googlemeet"],
)
url = session.mcp.url
What's happening:
  • You create a Google Meet only session through Composio
  • Composio returns an MCP HTTP URL that exposes Google Meet 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="Google Meet Assistant",
    goal="Help users interact with Google Meet through natural language commands",
    backstory=(
        "You are an expert assistant with access to Google Meet tools. "
        "You can perform various Google Meet 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 Google Meet 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 Google Meet 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 Google Meet 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_googlemeet_agent.py

Complete Code

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

python
# file: crewai_googlemeet_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 Google Meet session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["googlemeet"],
    )
    url = session.mcp.url

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

    # Create Google Meet assistant agent
    toolkit_agent = Agent(
        role="Google Meet Assistant",
        goal="Help users interact with Google Meet through natural language commands",
        backstory=(
            "You are an expert assistant with access to Google Meet tools. "
            "You can perform various Google Meet 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 Google Meet 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 Google Meet 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 Google Meet through Composio's Tool Router. The agent can perform Google Meet 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 Google Meet MCP Agent with another framework

OpenAI Agents SDK

OpenAI Agents SDK

Use Google Meet MCP with OpenAI Agents SDK

Claude Agent SDK

Claude Agent SDK

Use Google Meet MCP with Claude Agent SDK

Google ADK

Google ADK

Use Google Meet MCP with Google ADK

LangChain

LangChain

Use Google Meet MCP with LangChain

Vercel AI SDK

Vercel AI SDK

Use Google Meet MCP with Vercel AI SDK

Mastra AI

Mastra AI

Use Google Meet MCP with Mastra AI

LlamaIndex

LlamaIndex

Use Google Meet MCP with LlamaIndex

FAQ

What are the differences in Tool Router MCP and Google Meet MCP?

With a standalone Google Meet MCP server, the agents and LLMs can only access a fixed set of Google Meet tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Google Meet 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 Google Meet tools.

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

Yes, absolutely. You can configure which Google Meet 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 Google Meet data and credentials are handled as safely as possible.

Used by agents from

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