How to integrate Google Chat MCP with Pydantic AI

This guide walks you through connecting Google Chat to Pydantic AI 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 Pydantic AI 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.

45 Tools

Introduction

This guide walks you through connecting Google Chat to Pydantic AI 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 Pydantic AI 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:
  • How to set up your Composio API key and User ID
  • How to create a Composio Tool Router session for Google Chat
  • How to attach an MCP Server to a Pydantic AI agent
  • How to stream responses and maintain chat history
  • How to build a simple REPL-style chat interface to test your Google Chat workflows

What is Pydantic AI?

Pydantic AI is a Python framework for building AI agents with strong typing and validation. It leverages Pydantic's data validation capabilities to create robust, type-safe AI applications.

Key features include:

  • Type Safety: Built on Pydantic for automatic data validation
  • MCP Support: Native support for Model Context Protocol servers
  • Streaming: Built-in support for streaming responses
  • Async First: Designed for async/await patterns

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 step09 STEPS
1

Prerequisites

Before starting, make sure you have:
  • Python 3.9 or higher
  • A Composio account with an active API key
  • Basic familiarity with Python and async programming
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 pydantic-ai python-dotenv

Install the required libraries.

What's happening:

  • composio connects your agent to external SaaS tools like Google Chat
  • pydantic-ai lets you create structured AI agents with tool support
  • python-dotenv loads your environment variables securely from a .env file
4

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

Create a .env file in your project root.

What's happening:

  • COMPOSIO_API_KEY authenticates your agent to Composio's API
  • USER_ID associates your session with your account for secure tool access
  • OPENAI_API_KEY to access OpenAI LLMs
5

Import dependencies

python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerStreamableHTTP

load_dotenv()
What's happening:
  • We load environment variables and import required modules
  • Composio manages connections to Google Chat
  • MCPServerStreamableHTTP connects to the Google Chat MCP server endpoint
  • Agent from Pydantic AI lets you define and run the AI assistant
6

Create a Tool Router Session

python
async def main():
    api_key = os.getenv("COMPOSIO_API_KEY")
    user_id = os.getenv("USER_ID")
    if not api_key or not user_id:
        raise RuntimeError("Set COMPOSIO_API_KEY and USER_ID in your environment")

    # Create a Composio Tool Router session for Google Chat
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["google_chat"],
    )
    url = session.mcp.url
    if not url:
        raise ValueError("Composio session did not return an MCP URL")
What's happening:
  • We're creating a Tool Router session that gives your agent access to Google Chat tools
  • The create method takes the user ID and specifies which toolkits should be available
  • The returned session.mcp.url is the MCP server URL that your agent will use
7

Initialize the Pydantic AI Agent

python
# Attach the MCP server to a Pydantic AI Agent
google_chat_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
agent = Agent(
    "openai:gpt-5",
    toolsets=[google_chat_mcp],
    instructions=(
        "You are a Google Chat assistant. Use Google Chat tools to help users "
        "with their requests. Ask clarifying questions when needed."
    ),
)
What's happening:
  • The MCP client connects to the Google Chat endpoint
  • The agent uses GPT-5 to interpret user commands and perform Google Chat operations
  • The instructions field defines the agent's role and behavior
8

Build the chat interface

python
# Simple REPL with message history
history = []
print("Chat started! Type 'exit' or 'quit' to end.\n")
print("Try asking the agent to help you with Google Chat.\n")

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", flush=True)

    async with agent.run_stream(user_input, message_history=history) as stream_result:
        collected_text = ""
        async for chunk in stream_result.stream_output():
            text_piece = None
            if isinstance(chunk, str):
                text_piece = chunk
            elif hasattr(chunk, "delta") and isinstance(chunk.delta, str):
                text_piece = chunk.delta
            elif hasattr(chunk, "text"):
                text_piece = chunk.text
            if text_piece:
                collected_text += text_piece
        result = stream_result

    print(f"Agent: {collected_text}\n")
    history = result.all_messages()
What's happening:
  • The agent reads input from the terminal and streams its response
  • Google Chat API calls happen automatically under the hood
  • The model keeps conversation history to maintain context across turns
9

Run the application

python
if __name__ == "__main__":
    asyncio.run(main())
What's happening:
  • The asyncio loop launches the agent and keeps it running until you exit

Complete Code

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

python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerStreamableHTTP

load_dotenv()

async def main():
    api_key = os.getenv("COMPOSIO_API_KEY")
    user_id = os.getenv("USER_ID")
    if not api_key or not user_id:
        raise RuntimeError("Set COMPOSIO_API_KEY and USER_ID in your environment")

    # Create a Composio Tool Router session for Google Chat
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["google_chat"],
    )
    url = session.mcp.url
    if not url:
        raise ValueError("Composio session did not return an MCP URL")

    # Attach the MCP server to a Pydantic AI Agent
    google_chat_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
    agent = Agent(
        "openai:gpt-5",
        toolsets=[google_chat_mcp],
        instructions=(
            "You are a Google Chat assistant. Use Google Chat tools to help users "
            "with their requests. Ask clarifying questions when needed."
        ),
    )

    # Simple REPL with message history
    history = []
    print("Chat started! Type 'exit' or 'quit' to end.\n")
    print("Try asking the agent to help you with Google Chat.\n")

    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", flush=True)

        async with agent.run_stream(user_input, message_history=history) as stream_result:
            collected_text = ""
            async for chunk in stream_result.stream_output():
                text_piece = None
                if isinstance(chunk, str):
                    text_piece = chunk
                elif hasattr(chunk, "delta") and isinstance(chunk.delta, str):
                    text_piece = chunk.delta
                elif hasattr(chunk, "text"):
                    text_piece = chunk.text
                if text_piece:
                    collected_text += text_piece
            result = stream_result

        print(f"Agent: {collected_text}\n")
        history = result.all_messages()

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

Conclusion

You've built a Pydantic AI agent that can interact with Google Chat through Composio's Tool Router. With this setup, your agent can perform real Google Chat actions through natural language. You can extend this further by:
  • Adding other toolkits like Gmail, HubSpot, or Salesforce
  • Building a web-based chat interface around this agent
  • Using multiple MCP endpoints to enable cross-app workflows (for example, Gmail + Google Chat for workflow automation)
This architecture makes your AI agent "agent-native", able to securely use APIs in a unified, composable way without custom integrations.
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. Pydantic AI 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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