How to integrate Google Docs MCP with LangChain

This guide walks you through connecting Google Docs to LangChain 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 through natural language commands. This guide will help you understand how to give your LangChain 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.

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Google Docs is a cloud-based word processor that enables document creation and real-time collaboration. Its seamless sharing and version history make team editing and content management a breeze.

33 Tools10 Triggers

Introduction

This guide walks you through connecting Google Docs to LangChain 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 through natural language commands.

This guide will help you understand how to give your LangChain 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.

Also integrate Google Docs with

ChatGPTOpenAI Agents SDKClaude Agent SDKClaude CodeClaude CoworkCodexOpenCodeCursorVS CodeOpenClawHermesCLIGoogle ADKVercel AI SDKMastra AILlamaIndexCrewAI

TL;DR

Here's what you'll learn:
  • Get and set up your OpenAI and Composio API keys
  • Connect your Google Docs project to Composio
  • Create a Tool Router MCP session for Google Docs
  • Initialize an MCP client and retrieve Google Docs tools
  • Build a LangChain agent that can interact with Google Docs
  • Set up an interactive chat interface for testing

What is LangChain?

LangChain is a framework for developing applications powered by language models. It provides tools and abstractions for building agents that can reason, use tools, and maintain conversation context.

Key features include:

  • Agent Framework: Build agents that can use tools and make decisions
  • MCP Integration: Connect to external services through Model Context Protocol adapters
  • Memory Management: Maintain conversation history across interactions
  • Multi-Provider Support: Works with OpenAI, Anthropic, and other LLM providers

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.

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 step10 STEPS
1

Prerequisites

Before starting this tutorial, make sure you have:
  • Python 3.10 or higher installed on your system
  • A Composio account with an API key
  • An OpenAI 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

npm install @composio/langchain @langchain/core @langchain/openai @langchain/mcp-adapters dotenv

Install the required packages for LangChain with MCP support.

What's happening:

  • @composio/langchain provides Composio integration for LangChain
  • @langchain/mcp-adapters enables MCP client connections
  • @langchain/core is the core agent framework
  • dotenv/config loads environment variables
4

Set up environment variables

bash
COMPOSIO_API_KEY=your_composio_api_key_here
COMPOSIO_USER_ID=your_composio_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 your requests to Composio's API
  • COMPOSIO_USER_ID identifies the user for session management
  • OPENAI_API_KEY enables access to OpenAI's language models
5

Import dependencies

import { Composio } from '@composio/core';
import { LangchainProvider } from '@composio/langchain';
import { MultiServerMCPClient } from "@langchain/mcp-adapters";
import { createAgent } from "langchain";
import * as readline from 'readline';
import 'dotenv/config';

dotenv.config();
What's happening:
  • We're importing LangChain's MCP adapter and Composio SDK
  • The dotenv/config import loads environment variables from your .env file
  • This setup prepares the foundation for connecting LangChain with Google Docs functionality through MCP
6

Initialize Composio client

const composioApiKey = process.env.COMPOSIO_API_KEY;
const userId = process.env.COMPOSIO_USER_ID;

if (!composioApiKey) throw new Error('COMPOSIO_API_KEY is not set');
if (!userId) throw new Error('COMPOSIO_USER_ID is not set');

async function main() {
    const composio = new Composio({
        apiKey: composioApiKey as string,
        provider: new LangchainProvider()
    });
What's happening:
  • We're loading the COMPOSIO_API_KEY from environment variables and validating it exists
  • Creating a Composio instance that will manage our connection to Google Docs tools
  • Validating that COMPOSIO_USER_ID is also set before proceeding
7

Create a Tool Router session

const session = await composio.create(
    userId as string,
    {
        toolkits: ['googledocs']
    }
);

const url = session.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
  • This approach allows the agent to dynamically load and use Google Docs tools as needed
8

Configure the agent with the MCP URL

const client = new MultiServerMCPClient({
    "googledocs-agent": {
        transport: "http",
        url: url,
        headers: {
            "x-api-key": process.env.COMPOSIO_API_KEY
        }
    }
});

const tools = await client.getTools();

const agent = createAgent({ model: "gpt-5", tools });
What's happening:
  • We're creating a MultiServerMCPClient that connects to our Google Docs MCP server via HTTP
  • The client is configured with a name and the URL from our Tool Router session
  • getTools() retrieves all available Google Docs tools that the agent can use
  • We're creating a LangChain agent using the GPT-5 model
9

Set up interactive chat interface

let conversationHistory: any[] = [];

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

const rl = readline.createInterface({
    input: process.stdin,
    output: process.stdout,
    prompt: 'You: '
});

rl.prompt();

rl.on('line', async (userInput: string) => {
    const trimmedInput = userInput.trim();

    if (['exit', 'quit', 'bye'].includes(trimmedInput.toLowerCase())) {
        console.log("\nGoodbye!");
        rl.close();
        process.exit(0);
    }

    if (!trimmedInput) {
        rl.prompt();
        return;
    }

    conversationHistory.push({ role: "user", content: trimmedInput });
    console.log("\nAgent is thinking...\n");

    const response = await agent.invoke({ messages: conversationHistory });
    conversationHistory = response.messages;

    const finalResponse = response.messages[response.messages.length - 1]?.content;
    console.log(`Agent: ${finalResponse}\n`);
        
        rl.prompt();
    });

    rl.on('close', () => {
        console.log('\n👋 Session ended.');
        process.exit(0);
    });
What's happening:
  • We initialize an empty conversationHistory list to maintain context across interactions
  • A readline interface is used to continuously accept user input from the command line
  • When a user types a message, it's added to the conversation history and sent to the agent
  • The agent processes the request using the invoke() method with the full conversation history
  • Users can type 'exit', 'quit', or 'bye' to end the chat session gracefully
10

Run the application

main().catch((err) => {
    console.error('Fatal error:', err);
    process.exit(1);
});
What's happening:
  • We call the main() function to start the application

Complete Code

Here's the complete code to get you started with Google Docs and LangChain:

import { Composio } from '@composio/core';
import { LangchainProvider } from '@composio/langchain';
import { MultiServerMCPClient } from "@langchain/mcp-adapters";  
import { createAgent } from "langchain";
import * as readline from 'readline';
import 'dotenv/config';

const composioApiKey = process.env.COMPOSIO_API_KEY;
const userId = process.env.COMPOSIO_USER_ID;

if (!composioApiKey) throw new Error('COMPOSIO_API_KEY is not set');
if (!userId) throw new Error('COMPOSIO_USER_ID is not set');

async function main() {
    const composio = new Composio({
        apiKey: composioApiKey as string,
        provider: new LangchainProvider()
    });

    const session = await composio.create(
        userId as string,
        {
            toolkits: ['googledocs']
        }
    );

    const url = session.mcp.url;
    
    const client = new MultiServerMCPClient({
        "googledocs-agent": {
            transport: "http",
            url: url,
            headers: {
                "x-api-key": process.env.COMPOSIO_API_KEY
            }
        }
    });
    
    const tools = await client.getTools();
  
    const agent = createAgent({ model: "gpt-5", tools });
    
    let conversationHistory: any[] = [];
    
    console.log("Chat started! Type 'exit' or 'quit' to end the conversation.\n");
    console.log("Ask any Google Docs related question or task to the agent.\n");
    
    const rl = readline.createInterface({
        input: process.stdin,
        output: process.stdout,
        prompt: 'You: '
    });

    rl.prompt();

    rl.on('line', async (userInput: string) => {
        const trimmedInput = userInput.trim();
        
        if (['exit', 'quit', 'bye'].includes(trimmedInput.toLowerCase())) {
            console.log("\nGoodbye!");
            rl.close();
            process.exit(0);
        }
        
        if (!trimmedInput) {
            rl.prompt();
            return;
        }
        
        conversationHistory.push({ role: "user", content: trimmedInput });
        console.log("\nAgent is thinking...\n");
        
        const response = await agent.invoke({ messages: conversationHistory });
        conversationHistory = response.messages;
        
        const finalResponse = response.messages[response.messages.length - 1]?.content;
        console.log(`Agent: ${finalResponse}\n`);
        
        rl.prompt();
    });

    rl.on('close', () => {
        console.log('\nSession ended.');
        process.exit(0);
    });
}

main().catch((err) => {
    console.error('Fatal error:', err);
    process.exit(1);
});

Conclusion

You've successfully built a LangChain agent that can interact with Google Docs through Composio's Tool Router.

Key features of this implementation:

  • Dynamic tool loading through Composio's Tool Router
  • Conversation history maintenance for context-aware responses
  • Async Python provides clean, efficient execution of agent workflows
You can extend this further by adding error handling, implementing specific business logic, or integrating additional Composio toolkits to create multi-app workflows.
TOOLS & TRIGGERS

Supported Tools and Triggers

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

Copy Google Document

Tool to create a copy of an existing Google Document.

Create a document

Creates 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 Markdown

Creates a new Google Docs document, optionally initializing it with a title and content provided as Markdown text.

Create Footer

Tool to create a new footer in a Google Document.

Create Footnote

Tool to create a new footnote in a Google Document.

Create Header

Tool to create a new header in a Google Document, optionally with text content.

Create Named Range

Tool to create a new named range in a Google Document.

Create Paragraph Bullets

Tool to add bullets to paragraphs within a specified range in a Google Document.

Delete Content Range in Document

Tool to delete a range of content from a Google Document.

Delete Footer

Tool to delete a footer from a Google Document.

Delete Header

Deletes the header from the specified section or the default header if no section is specified.

Delete Named Range

Tool to delete a named range from a Google Document.

Delete Paragraph Bullets

Tool to remove bullets from paragraphs within a specified range in a Google Document.

Delete Table Column

Tool to delete a column from a table in a Google Document.

Delete Table Row

Tool to delete a row from a table in a Google Document.

Export Google Doc as PDF

Tool to export a Google Docs file as PDF using the Google Drive API.

Get document by id

Retrieves an existing Google Document by its ID; will error if the document is not found.

Get document plain text

Retrieve a Google Doc by ID and return a best-effort plain-text rendering.

Insert Inline Image

Tool to insert an image from a given URI at a specified location in a Google Document as an inline image.

Insert Page Break

Tool to insert a page break into a Google Document.

Insert Table in Google Doc

Tool to insert a table into a Google Document.

Insert Table Column

Tool to insert a new column into a table in a Google Document.

Insert Text into Document

Tool to insert a string of text at a specified location within a Google Document.

Get Charts from Spreadsheet

Tool to retrieve a list of all charts from a specified Google Sheets spreadsheet.

Replace All Text in Document

Tool to replace all occurrences of a specified text string with another text string throughout a Google Document.

Replace Image in Document

Tool to replace a specific image in a document with a new image from a URI.

Search Documents

Search for Google Documents using various filters including name, content, date ranges, and more.

Unmerge Table Cells

Tool to unmerge previously merged cells in a table.

Update Document Markdown

Replaces the entire content of an existing Google Docs document with new Markdown text; requires edit permissions for the document.

Update Document Section Markdown

Tool to insert or replace a section of a Google Docs document with Markdown content.

Update Document Style

Tool to update the overall document style, such as page size, margins, and default text direction.

Update existing document

Applies programmatic edits, such as text insertion, deletion, or formatting, to a specified Google Doc using the `batchUpdate` API method.

Update Table Row Style

Tool to update the style of a table row in a Google Document.

FRAMEWORKS

How to build Google Docs MCP Agent with another framework

ChatGPT logo

ChatGPT

Use Google Docs MCP with ChatGPT

OpenAI Agents SDK logo

OpenAI Agents SDK

Use Google Docs MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use Google Docs MCP with Claude Agent SDK

Claude Code logo

Claude Code

Use Google Docs MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use Google Docs MCP with Claude Cowork

Codex logo

Codex

Use Google Docs MCP with Codex

Cursor logo

Cursor

Use Google Docs MCP with Cursor

OpenClaw logo

OpenClaw

Use Google Docs MCP with OpenClaw

Hermes logo

Hermes

Use Google Docs MCP with Hermes

CLI logo

CLI

Use Google Docs MCP with CLI

Google ADK logo

Google ADK

Use Google Docs MCP with Google ADK

Vercel AI SDK logo

Vercel AI SDK

Use Google Docs MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use Google Docs MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use Google Docs MCP with LlamaIndex

CrewAI logo

CrewAI

Use Google Docs MCP with CrewAI

OpenCode logo

OpenCode

Use Google Docs MCP with OpenCode

VS Code logo

VS Code

Use Google Docs MCP with VS Code

FAQ

Frequently asked questions

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.

Yes, you can. LangChain 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.

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.

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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Karan skipped his own birthday party to fix our critical issue. It was 10pm and he diverted his Waymo to help us instead. This really sets the bar — it shows the commitment you need when users rely on your software.

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A lot of students tell us that the moment their connected tools start talking to each other inside Opennote feels almost magical. The agent just knows them, and it's immensely helped keep new users on the platform.

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Co-founder, Opennote

We chose Composio over Pipedream because it delivered depth where it mattered — niche tools and tricky edge cases other platforms simply ignored. That gave us confidence to scale without compromising.

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CEO, Zams

As a solo builder, shipping fast is life or death. The only way I can outcompete incumbents is by outmanoeuvring them. Getting bogged down managing agent auth would have been a death sentence.

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Founder, Extra Thursday

Before Composio, adding tool integrations was slow and resource-intensive. Each one could take weeks of engineering time, and maintaining them meant constantly keeping up with API changes.

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Founder & CEO, SwarmZero

With hands-on help from their founder, we integrated Gmail and Google Drive in just 30 minutes. This level of personal support and commitment is exactly what startups should strive for.

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