How to integrate Google Docs MCP with Pydantic AI

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Introduction

This guide walks you through connecting Google Docs to Pydantic AI using the Composio tool router. By the end, you'll have a working Google Docs agent that can create a new meeting notes document, copy last week's project summary template, add bullet points to the action items section, delete the footer from my current draft through natural language commands.

This guide will help you understand how to give your Pydantic AI agent real control over a Google Docs account through Composio's Google Docs 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:
  • How to set up your Composio API key and User ID
  • How to create a Composio Tool Router session for Google Docs
  • 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 Docs 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 Docs MCP server, and what's possible with it?

The Google Docs 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 Docs account. It provides structured and secure access to your documents, so your agent can create, copy, edit, and organize Google Docs on your behalf.

  • Automated document creation and duplication: Let your agent generate new Google Docs from scratch or copy existing documents to quickly use templates or preserve originals.
  • Rich content editing and formatting: Direct your agent to add headers, footers, footnotes, bullet lists, and more—making it easy to update and format documents programmatically.
  • Targeted content manipulation: Have your agent delete specific content ranges, paragraphs, or sections within any document to keep your files up to date.
  • Named range management: Empower your agent to create and manage named ranges for easier referencing, collaboration, and advanced document workflows.
  • Markdown-based document generation: Allow the agent to create new Google Docs directly from markdown content, streamlining content migration from other tools or sources.

Supported Tools & Triggers

Tools
Triggers
Copy Google DocumentTool to create a copy of an existing google document.
Create a documentCreates a new google docs document using the provided title as filename and inserts the initial text at the beginning if non-empty, returning the document's id and metadata (excluding body content).
Create Document MarkdownCreates a new google docs document, optionally initializing it with a title and content provided as markdown text.
Create FooterTool to create a new footer in a google document.
Create FootnoteTool to create a new footnote in a google document.
Create HeaderTool to create a new header in a google document.
Create Named RangeTool to create a new named range in a google document.
Create Paragraph BulletsTool to add bullets to paragraphs within a specified range in a google document.
Delete Content Range in DocumentTool to delete a range of content from a google document.
Delete FooterTool to delete a footer from a google document.
Delete HeaderDeletes the header from the specified section or the default header if no section is specified.
Delete Named RangeTool to delete a named range from a google document.
Delete Paragraph BulletsTool to remove bullets from paragraphs within a specified range in a google document.
Delete TableTool to delete an entire table from a google document.
Delete Table ColumnTool to delete a column from a table in a google document.
Delete Table RowTool to delete a row from a table in a google document.
Get Charts from SpreadsheetTool to retrieve a list of all charts from a specified google sheets spreadsheet.
Get document by idRetrieves an existing google document by its id; will error if the document is not found.
Insert Inline ImageTool to insert an image from a given uri at a specified location in a google document as an inline image.
Insert Page BreakTool to insert a page break into a google document.
Insert Table in Google DocTool to insert a table into a google document.
Insert Table ColumnTool to insert a new column into a table in a google document.
Insert Text into DocumentTool to insert a string of text at a specified location within a google document.
List Charts from SpreadsheetTool to retrieve a list of charts with their ids and metadata from a google sheets spreadsheet.
Replace All Text in DocumentTool to replace all occurrences of a specified text string with another text string throughout a google document.
Replace Image in DocumentTool to replace a specific image in a document with a new image from a uri.
Search DocumentsSearch for google documents using various filters including name, content, date ranges, and more.
Unmerge Table CellsTool to unmerge previously merged cells in a table.
Update Document MarkdownReplaces the entire content of an existing google docs document with new markdown text; requires edit permissions for the document.
Update Document StyleTool to update the overall document style, such as page size, margins, and default text direction.
Update existing documentApplies programmatic edits, such as text insertion, deletion, or formatting, to a specified google doc using the `batchupdate` api method.
Update Table Row StyleTool to update the style of a table row in a google document.

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 with an active API key
  • Basic familiarity with Python and async programming

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 pydantic-ai python-dotenv

Install the required libraries.

What's happening:

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

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

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 Docs
  • MCPServerStreamableHTTP connects to the Google Docs MCP server endpoint
  • Agent from Pydantic AI lets you define and run the AI assistant

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 Docs
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["googledocs"],
    )
    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 Docs 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

Initialize the Pydantic AI Agent

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

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 Docs.\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 Docs API calls happen automatically under the hood
  • The model keeps conversation history to maintain context across turns

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 Docs 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 Docs
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["googledocs"],
    )
    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
    googledocs_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
    agent = Agent(
        "openai:gpt-5",
        toolsets=[googledocs_mcp],
        instructions=(
            "You are a Google Docs assistant. Use Google Docs 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 Docs.\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 Docs through Composio's Tool Router. With this setup, your agent can perform real Google Docs 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 Docs for workflow automation)
This architecture makes your AI agent "agent-native", able to securely use APIs in a unified, composable way without custom integrations.

How to build Google Docs MCP Agent with another framework

OpenAI Agents SDK

OpenAI Agents SDK

Use Google Docs MCP with OpenAI Agents SDK

Claude Agent SDK

Claude Agent SDK

Use Google Docs MCP with Claude Agent SDK

Google ADK

Google ADK

Use Google Docs MCP with Google ADK

LangChain

LangChain

Use Google Docs MCP with LangChain

Vercel AI SDK

Vercel AI SDK

Use Google Docs MCP with Vercel AI SDK

Mastra AI

Mastra AI

Use Google Docs MCP with Mastra AI

LlamaIndex

LlamaIndex

Use Google Docs MCP with LlamaIndex

CrewAI

CrewAI

Use Google Docs MCP with CrewAI

FAQ

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

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

Can I use Tool Router MCP with Pydantic AI?

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 Docs tools.

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

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

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