How to integrate Google Chat MCP with Autogen

This guide walks you through connecting Google Chat to AutoGen using the Composio tool router. By the end, you'll have a working Google Chat agent that can summarize recent messages in project space, send standup reminder to engineering space, list members of support chat space through natural language commands. This guide will help you understand how to give your AutoGen agent real control over a Google Chat account through Composio's Google Chat MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

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Google Chat is Google Workspace's messaging and collaboration service for teams. It keeps conversations, spaces, files, and work updates in one shared place.

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Introduction

This guide walks you through connecting Google Chat to AutoGen using the Composio tool router. By the end, you'll have a working Google Chat agent that can summarize recent messages in project space, send standup reminder to engineering space, list members of support chat space through natural language commands.

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

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

Also integrate Google Chat with

OpenAI Agents SDKClaude Agent SDKClaude CodeClaude CoworkCodexOpenClawHermesCLIGoogle ADKLangChainVercel AI SDKMastra AILlamaIndexCrewAI

TL;DR

Here's what you'll learn:
  • Get and set up your OpenAI and Composio API keys
  • Install the required dependencies for Autogen and Composio
  • Initialize Composio and create a Tool Router session for Google Chat
  • Wire that MCP URL into Autogen using McpWorkbench and StreamableHttpServerParams
  • Configure an Autogen AssistantAgent that can call Google Chat tools
  • Run a live chat loop where you ask the agent to perform Google Chat operations

What is AutoGen?

Autogen is a framework for building multi-agent conversational AI systems from Microsoft. It enables you to create agents that can collaborate, use tools, and maintain complex workflows.

Key features include:

  • Multi-Agent Systems: Build collaborative agent workflows
  • MCP Workbench: Native support for Model Context Protocol tools
  • Streaming HTTP: Connect to external services through streamable HTTP
  • AssistantAgent: Pre-built agent class for tool-using assistants

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

The Google Chat 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 Chat account. It provides structured and secure access so your agent can perform Google Chat operations on your behalf.

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

What is Composio SDK?

Composio's Composio SDK 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 Composio SDK

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

How the Composio SDK works

The Composio SDK 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

Step by step08 STEPS
1

Prerequisites

You will need:

  • A Composio API key
  • An OpenAI API key (used by Autogen's OpenAIChatCompletionClient)
  • A Google Chat account you can connect to Composio
  • Some basic familiarity with Autogen and Python async
2

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.
3

Install dependencies

bash
pip install composio python-dotenv
pip install autogen-agentchat autogen-ext-openai autogen-ext-tools

Install Composio, Autogen extensions, and dotenv.

What's happening:

  • composio connects your agent to Google Chat via MCP
  • autogen-agentchat provides the AssistantAgent class
  • autogen-ext-openai provides the OpenAI model client
  • autogen-ext-tools provides MCP workbench support

4

Set up environment variables

bash
COMPOSIO_API_KEY=your-composio-api-key
OPENAI_API_KEY=your-openai-api-key
USER_ID=your-user-identifier@example.com

Create a .env file in your project folder.

What's happening:

  • COMPOSIO_API_KEY is required to talk to Composio
  • OPENAI_API_KEY is used by Autogen's OpenAI client
  • USER_ID is how Composio identifies which user's Google Chat connections to use
5

Import dependencies and create Tool Router session

python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio

from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient
from autogen_ext.tools.mcp import McpWorkbench, StreamableHttpServerParams

load_dotenv()

async def main():
    # Initialize Composio and create a Google Chat session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["google_chat"]
    )
    url = session.mcp.url
What's happening:
  • load_dotenv() reads your .env file
  • Composio(api_key=...) initializes the SDK
  • create(...) creates a Tool Router session that exposes Google Chat tools
  • session.mcp.url is the MCP endpoint that Autogen will connect to
6

Configure MCP parameters for Autogen

python
# Configure MCP server parameters for Streamable HTTP
server_params = StreamableHttpServerParams(
    url=url,
    timeout=30.0,
    sse_read_timeout=300.0,
    terminate_on_close=True,
    headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")}
)

Autogen expects parameters describing how to talk to the MCP server. That is what StreamableHttpServerParams is for.

What's happening:

  • url points to the Tool Router MCP endpoint from Composio
  • timeout is the HTTP timeout for requests
  • sse_read_timeout controls how long to wait when streaming responses
  • terminate_on_close=True cleans up the MCP server process when the workbench is closed
7

Create the model client and agent

python
# Create model client
model_client = OpenAIChatCompletionClient(
    model="gpt-5",
    api_key=os.getenv("OPENAI_API_KEY")
)

# Use McpWorkbench as context manager
async with McpWorkbench(server_params) as workbench:
    # Create Google Chat assistant agent with MCP tools
    agent = AssistantAgent(
        name="google_chat_assistant",
        description="An AI assistant that helps with Google Chat operations.",
        model_client=model_client,
        workbench=workbench,
        model_client_stream=True,
        max_tool_iterations=10
    )

What's happening:

  • OpenAIChatCompletionClient wraps the OpenAI model for Autogen
  • McpWorkbench connects the agent to the MCP tools
  • AssistantAgent is configured with the Google Chat tools from the workbench
8

Run the interactive chat loop

python
print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
print("Ask any Google Chat related question or task to the agent.\n")

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

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

    if not user_input:
        continue

    print("\nAgent is thinking...\n")

    # Run the agent with streaming
    try:
        response_text = ""
        async for message in agent.run_stream(task=user_input):
            if hasattr(message, "content") and message.content:
                response_text = message.content

        # Print the final response
        if response_text:
            print(f"Agent: {response_text}\n")
        else:
            print("Agent: I encountered an issue processing your request.\n")

    except Exception as e:
        print(f"Agent: Sorry, I encountered an error: {str(e)}\n")
What's happening:
  • The script prompts you in a loop with You:
  • Autogen passes your input to the model, which decides which Google Chat tools to call via MCP
  • agent.run_stream(...) yields streaming messages as the agent thinks and calls tools
  • Typing exit, quit, or bye ends the loop

Complete Code

Here's the complete code to get you started with Google Chat and AutoGen:

python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio

from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient
from autogen_ext.tools.mcp import McpWorkbench, StreamableHttpServerParams

load_dotenv()

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

    # Configure MCP server parameters for Streamable HTTP
    server_params = StreamableHttpServerParams(
        url=url,
        timeout=30.0,
        sse_read_timeout=300.0,
        terminate_on_close=True,
        headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")}
    )

    # Create model client
    model_client = OpenAIChatCompletionClient(
        model="gpt-5",
        api_key=os.getenv("OPENAI_API_KEY")
    )

    # Use McpWorkbench as context manager
    async with McpWorkbench(server_params) as workbench:
        # Create Google Chat assistant agent with MCP tools
        agent = AssistantAgent(
            name="google_chat_assistant",
            description="An AI assistant that helps with Google Chat operations.",
            model_client=model_client,
            workbench=workbench,
            model_client_stream=True,
            max_tool_iterations=10
        )

        print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
        print("Ask any Google Chat related question or task to the agent.\n")

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

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

            if not user_input:
                continue

            print("\nAgent is thinking...\n")

            # Run the agent with streaming
            try:
                response_text = ""
                async for message in agent.run_stream(task=user_input):
                    if hasattr(message, 'content') and message.content:
                        response_text = message.content

                # Print the final response
                if response_text:
                    print(f"Agent: {response_text}\n")
                else:
                    print("Agent: I encountered an issue processing your request.\n")

            except Exception as e:
                print(f"Agent: Sorry, I encountered an error: {str(e)}\n")

if __name__ == "__main__":
    asyncio.run(main())

Conclusion

You now have an Autogen assistant wired into Google Chat through Composio's Tool Router and MCP. From here you can:
  • Add more toolkits to the toolkits list, for example notion or hubspot
  • Refine the agent description to point it at specific workflows
  • Wrap this script behind a UI, Slack bot, or internal tool
Once the pattern is clear for Google Chat, you can reuse the same structure for other MCP-enabled apps with minimal code changes.
TOOLS

Supported Tools

Every Google Chat action and event your agent gets out of the box.

Complete Space Import

Completes the import process for an import-mode Google Chat space and makes it visible to users.

Create Custom Emoji

Creates a custom emoji in Google Chat for use within an organization.

Create Space Member

Creates a membership for a user, Chat app, or Google Group in a space.

Create Message

Creates a message in a Google Chat space.

Create Reaction

Creates an emoji reaction on a Google Chat message.

Create section

Creates a custom section in Google Chat for organizing conversations in the navigation panel.

Create Space

Creates a named space or group chat in Google Chat.

Delete Custom Emoji

Deletes a custom emoji from Google Chat.

Delete Member from Space

Removes a user, Google Group, or app from a space.

Delete Message

Deletes a message from a Google Chat space.

Delete Reaction

Deletes a reaction to a message.

Delete section

Deletes a custom section from Google Chat by its ID.

Delete space

Deletes a named space from Google Chat.

Download Media

Downloads the bytes of a Google Chat message attachment via the media API.

Find Direct Message

Returns the existing direct message space with the specified user.

Find Group Chats

Finds all group chat spaces that contain exactly the calling user and the specified users.

Get Attachment

Gets the metadata of a Google Chat message attachment.

Get Custom Emoji

Returns details about a custom emoji in Google Chat.

Get Chat Space Member

Returns details about a membership in a space.

Get Message

Returns details about a specific message in a Google Chat space.

Get Space

Returns details about a specific Google Chat space including configuration, membership count, and access settings.

Get Space Event

Returns an event from a Google Chat space.

Get Space Notification Setting

Gets the notification settings for a user in a specific space.

Get space read state

Returns details about a user's read state within a space.

Get thread read state

Returns details about a user's read state within a thread.

List custom emojis

Lists custom emojis visible to the authenticated user in Google Chat.

List Space Members

Lists memberships in a space.

List Messages

Lists messages in a space that the authenticated user is a member of.

List reactions on a message

Lists all reactions on a specific message in a Google Chat space.

List Section Items

Lists all items (such as spaces) within a specified section of a user's Google Chat.

List Sections

Lists all sections available to the authenticated user in Google Chat.

List Space Events

Lists events from a Google Chat space.

List Spaces

Lists spaces the authenticated user is a member of in Google Chat.

Move Section Item

Moves a space from one section to another in Google Chat.

Position Section in Sidebar

Changes the sort order of a section in the Google Chat sidebar.

Replace Message (Full)

Replaces an existing message in a Google Chat space using full replacement.

Search Spaces

Searches for spaces across a Google Workspace organization using administrator privileges.

Setup Space

Creates a space and adds specified users and groups to it.

Update Member

Updates a membership in a Google Chat space, such as changing a member's role between member and manager.

Update Message

Updates a message in a Google Chat space, modifying its text, cards, or other properties.

Update section

Updates a section's display name in Google Chat.

Update Space

Updates a Google Chat space's configuration including display name, description, guidelines, history settings, access settings, and permission settings.

Update Space Notification Setting

Updates the notification settings for a user in a space.

Update Space Read State

Updates a user's read state within a space, used to mark messages as read or unread.

Upload Media Attachment

Uploads a file as an attachment to a Google Chat space using the multipart media upload endpoint.

FRAMEWORKS

How to build Google Chat MCP Agent with another framework

OpenAI Agents SDK logo

OpenAI Agents SDK

Use Google Chat MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use Google Chat MCP with Claude Agent SDK

Claude Code logo

Claude Code

Use Google Chat MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use Google Chat MCP with Claude Cowork

Codex logo

Codex

Use Google Chat MCP with Codex

OpenClaw logo

OpenClaw

Use Google Chat MCP with OpenClaw

Hermes logo

Hermes

Use Google Chat MCP with Hermes

CLI logo

CLI

Use Google Chat MCP with CLI

Google ADK logo

Google ADK

Use Google Chat MCP with Google ADK

LangChain logo

LangChain

Use Google Chat MCP with LangChain

Vercel AI SDK logo

Vercel AI SDK

Use Google Chat MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use Google Chat MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use Google Chat MCP with LlamaIndex

CrewAI logo

CrewAI

Use Google Chat MCP with CrewAI

FAQ

Frequently asked questions

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

Yes, you can. Autogen 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 Chat tools.

Yes, absolutely. You can configure which Google Chat 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.

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 Chat data and credentials are handled as safely as possible.

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