# How to integrate Google Docs MCP with Vercel AI SDK v6 ```json { "title": "How to integrate Google Docs MCP with Vercel AI SDK v6", "toolkit": "Google Docs", "toolkit_slug": "googledocs", "framework": "Vercel AI SDK", "framework_slug": "ai-sdk", "url": "https://composio.dev/toolkits/googledocs/framework/ai-sdk", "markdown_url": "https://composio.dev/toolkits/googledocs/framework/ai-sdk.md", "updated_at": "2026-05-06T08:14:17.274Z" } ``` ## Introduction This guide walks you through connecting Google Docs to Vercel AI SDK v6 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 Vercel AI SDK 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 - [ChatGPT](https://composio.dev/toolkits/googledocs/framework/chatgpt) - [OpenAI Agents SDK](https://composio.dev/toolkits/googledocs/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/googledocs/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/googledocs/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/googledocs/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/googledocs/framework/codex) - [Cursor](https://composio.dev/toolkits/googledocs/framework/cursor) - [VS Code](https://composio.dev/toolkits/googledocs/framework/vscode) - [OpenCode](https://composio.dev/toolkits/googledocs/framework/opencode) - [OpenClaw](https://composio.dev/toolkits/googledocs/framework/openclaw) - [Hermes](https://composio.dev/toolkits/googledocs/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/googledocs/framework/cli) - [Google ADK](https://composio.dev/toolkits/googledocs/framework/google-adk) - [LangChain](https://composio.dev/toolkits/googledocs/framework/langchain) - [Mastra AI](https://composio.dev/toolkits/googledocs/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/googledocs/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/googledocs/framework/crew-ai) ## TL;DR Here's what you'll learn: - How to set up and configure a Vercel AI SDK agent with Google Docs integration - Using Composio's Tool Router to dynamically load and access Google Docs tools - Creating an MCP client connection using HTTP transport - Building an interactive CLI chat interface with conversation history management - Handling tool calls and results within the Vercel AI SDK framework ## What is Vercel AI SDK? The Vercel AI SDK is a TypeScript library for building AI-powered applications. It provides tools for creating agents that can use external services and maintain conversation state. Key features include: - streamText: Core function for streaming responses with real-time tool support - MCP Client: Built-in support for Model Context Protocol via @ai-sdk/mcp - Step Counting: Control multi-step tool execution with stopWhen: stepCountIs() - OpenAI Provider: Native integration with OpenAI models ## 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 | Tool slug | Name | Description | |---|---|---| | `GOOGLEDOCS_COPY_DOCUMENT` | Copy Google Document | Tool to create a copy of an existing google document. use this to duplicate a document, for example, when using an existing document as a template. the copied document will have a default title (e.g., 'copy of [original title]') if no new title is provided, and will be placed in the user's root google drive folder. | | `GOOGLEDOCS_CREATE_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). | | `GOOGLEDOCS_CREATE_DOCUMENT_MARKDOWN` | Create Document Markdown | Creates a new google docs document, optionally initializing it with a title and content provided as markdown text. | | `GOOGLEDOCS_CREATE_FOOTER` | Create Footer | Tool to create a new footer in a google document. use when you need to add a footer, optionally specifying its type and the section it applies to. | | `GOOGLEDOCS_CREATE_FOOTNOTE` | Create Footnote | Tool to create a new footnote in a google document. use this when you need to add a footnote at a specific location or at the end of the document body. | | `GOOGLEDOCS_CREATE_HEADER` | Create Header | Tool to create a new header in a google document. use this tool when you need to add a header to a document, optionally specifying the section it applies to. | | `GOOGLEDOCS_CREATE_NAMED_RANGE` | Create Named Range | Tool to create a new named range in a google document. use this to assign a name to a specific part of the document for easier reference or programmatic manipulation. | | `GOOGLEDOCS_CREATE_PARAGRAPH_BULLETS` | Create Paragraph Bullets | Tool to add bullets to paragraphs within a specified range in a google document. use when you need to format a list or a set of paragraphs as bullet points. | | `GOOGLEDOCS_DELETE_CONTENT_RANGE` | Delete Content Range in Document | Tool to delete a range of content from a google document. use when you need to remove a specific portion of text or other structural elements within a document. | | `GOOGLEDOCS_DELETE_FOOTER` | Delete Footer | Tool to delete a footer from a google document. use when you need to remove a footer from a specific section or the default footer. | | `GOOGLEDOCS_DELETE_HEADER` | Delete Header | Deletes the header from the specified section or the default header if no section is specified. use this tool to remove a header from a google document. | | `GOOGLEDOCS_DELETE_NAMED_RANGE` | Delete Named Range | Tool to delete a named range from a google document. use when you need to remove a previously defined named range by its id or name. | | `GOOGLEDOCS_DELETE_PARAGRAPH_BULLETS` | Delete Paragraph Bullets | Tool to remove bullets from paragraphs within a specified range in a google document. use when you need to clear bullet formatting from a section of a document. | | `GOOGLEDOCS_DELETE_TABLE` | Delete Table | Tool to delete an entire table from a google document. use when you have the document id and the specific start and end index of the table element to be removed. the table's range can be found by inspecting the document's content structure. | | `GOOGLEDOCS_DELETE_TABLE_COLUMN` | Delete Table Column | Tool to delete a column from a table in a google document. use this tool when you need to remove a specific column from an existing table within a document. | | `GOOGLEDOCS_DELETE_TABLE_ROW` | Delete Table Row | Tool to delete a row from a table in a google document. use when you need to remove a specific row from an existing table. | | `GOOGLEDOCS_GET_CHARTS_FROM_SPREADSHEET` | Get Charts from Spreadsheet | Tool to retrieve a list of all charts from a specified google sheets spreadsheet. use when you need to get chart ids and their specifications for embedding or referencing elsewhere, such as in google docs. | | `GOOGLEDOCS_GET_DOCUMENT_BY_ID` | Get document by id | Retrieves an existing google document by its id; will error if the document is not found. | | `GOOGLEDOCS_INSERT_INLINE_IMAGE` | Insert Inline Image | Tool to insert an image from a given uri at a specified location in a google document as an inline image. use when you need to add an image to a document programmatically. | | `GOOGLEDOCS_INSERT_PAGE_BREAK` | Insert Page Break | Tool to insert a page break into a google document. use when you need to start new content on a fresh page, such as at the end of a chapter or section. | | `GOOGLEDOCS_INSERT_TABLE_ACTION` | Insert Table in Google Doc | Tool to insert a table into a google document. use when you need to add a new table at a specific location or at the end of a segment (like document body, header, or footer) in a document. | | `GOOGLEDOCS_INSERT_TABLE_COLUMN` | Insert Table Column | Tool to insert a new column into a table in a google document. use this tool when you need to add a column to an existing table at a specific location. | | `GOOGLEDOCS_INSERT_TEXT_ACTION` | Insert Text into Document | Tool to insert a string of text at a specified location within a google document. use when you need to add new text content to an existing document. | | `GOOGLEDOCS_LIST_SPREADSHEET_CHARTS_ACTION` | List Charts from Spreadsheet | Tool to retrieve a list of charts with their ids and metadata from a google sheets spreadsheet. use to identify charts available for embedding into google docs. | | `GOOGLEDOCS_REPLACE_ALL_TEXT` | Replace All Text in Document | Tool to replace all occurrences of a specified text string with another text string throughout a google document. use when you need to perform a global find and replace operation within a document. | | `GOOGLEDOCS_REPLACE_IMAGE` | Replace Image in Document | Tool to replace a specific image in a document with a new image from a uri. use when you need to update an existing image within a google doc. | | `GOOGLEDOCS_SEARCH_DOCUMENTS` | Search Documents | Search for google documents using various filters including name, content, date ranges, and more. | | `GOOGLEDOCS_UNMERGE_TABLE_CELLS` | Unmerge Table Cells | Tool to unmerge previously merged cells in a table. use this when you need to revert merged cells in a google document table back to their individual cell states. | | `GOOGLEDOCS_UPDATE_DOCUMENT_MARKDOWN` | Update Document Markdown | Replaces the entire content of an existing google docs document with new markdown text; requires edit permissions for the document. | | `GOOGLEDOCS_UPDATE_DOCUMENT_STYLE` | Update Document Style | Tool to update the overall document style, such as page size, margins, and default text direction. use when you need to modify the global style settings of a google document. | | `GOOGLEDOCS_UPDATE_EXISTING_DOCUMENT` | Update existing document | Applies programmatic edits, such as text insertion, deletion, or formatting, to a specified google doc using the `batchupdate` api method. | | `GOOGLEDOCS_UPDATE_TABLE_ROW_STYLE` | Update Table Row Style | Tool to update the style of a table row in a google document. use when you need to modify the appearance of specific rows within a table, such as setting minimum row height or marking rows as headers. | ## Supported Triggers | Trigger slug | Name | Description | |---|---|---| | `GOOGLEDOCS_DOCUMENT_CREATED_TRIGGER` | New Document Created | Triggers when a new Google Doc is created. This trigger monitors Google Docs and fires when new documents are detected. Uses timestamp filtering to efficiently poll for new documents. | | `GOOGLEDOCS_DOCUMENT_DELETED_TRIGGER` | Document Deleted | Triggers when an existing Google Doc is deleted (moved to trash). This trigger monitors Google Docs and fires when documents are trashed. | | `GOOGLEDOCS_DOCUMENT_PLACEHOLDER_FILLED_TRIGGER` | Document Placeholder Filled | Triggers when a Google Doc's plain text changes such that a configured placeholder token/pattern is no longer present (i.e., the document has been filled in). This trigger monitors a specific Google Doc and fires when a placeholder pattern that was previously present is no longer found in the document's plain text. | | `GOOGLEDOCS_DOCUMENT_SEARCH_UPDATE_TRIGGER` | Document Search Update | Triggers when a Google Doc matching a user-defined search query is newly created or updated since the last poll. This trigger uses timestamp filtering to efficiently monitor documents. | | `GOOGLEDOCS_DOCUMENT_STRUCTURE_CHANGED_TRIGGER` | Document Structure Changed | Triggers when a Google Doc's structure changes (headers/footers added/removed, tables/images count changes). This trigger monitors a specific document for structural changes like: - Headers added or removed - Footers added or removed - Tables added or removed - Images (inline objects) added or removed - Positioned objects added or removed - Footnotes added or removed | | `GOOGLEDOCS_DOCUMENT_UPDATED_TRIGGER` | Document Updated | Triggers when an existing Google Doc is updated or modified. This trigger monitors Google Docs and fires when documents are updated. | | `GOOGLEDOCS_DOCUMENT_WORD_COUNT_THRESHOLD_TRIGGER` | Document Word Count Threshold | Triggers when a Google Doc's word/character count crosses a user-defined threshold. This trigger monitors a specific Google Doc and fires when its word or character count becomes greater than or equal to the configured threshold value. | | `GOOGLEDOCS_FOLDER_CREATED_TRIGGER` | New Folder Created in Root | Triggers when a new folder is created in the root folder of Google Drive. This trigger monitors Google Drive and fires when new folders are detected in the root directory. | | `GOOGLEDOCS_KEYWORD_DETECTED_TRIGGER` | Keyword Detected in Document | Triggers when a specific keyword or phrase first appears in a Google Doc. This trigger monitors a Google Doc and fires once when the specified keyword is detected. After the keyword is found, the trigger will not fire again until reset. | | `GOOGLEDOCS_PAGE_ADDED_TRIGGER` | New Document Added | Triggers when a new Google Doc is added/created. This trigger monitors Google Docs and fires when new documents are detected. | ## Creating MCP Server - Stand-alone vs Composio SDK The Google Docs MCP server is an implementation of the Model Context Protocol that connects your AI agent to Google Docs. It provides structured and secure access so your agent can perform Google Docs operations on your behalf through a secure, permission-based interface. With Composio's managed implementation, you don't have to create your own developer app. For production, if you're building an end product, we recommend using your own credentials. The managed server helps you prototype fast and go from 0-1 faster. ## Step-by-step Guide ### 1. Prerequisites Before you begin, make sure you have: - Node.js and npm installed - A Composio account with API key - An OpenAI API key ### 1. Getting API Keys for OpenAI and Composio OpenAI API Key - Go to the [OpenAI dashboard](https://platform.openai.com/settings/organization/api-keys) 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](https://dashboard.composio.dev?utm_source=toolkits&utm_medium=framework_docs). - Navigate to your API settings and generate a new API key. - Store this key securely as you'll need it for authentication. ### 2. Install required dependencies First, install the necessary packages for your project. What you're installing: - @ai-sdk/openai: Vercel AI SDK's OpenAI provider - @ai-sdk/mcp: MCP client for Vercel AI SDK - @composio/core: Composio SDK for tool integration - ai: Core Vercel AI SDK - dotenv: Environment variable management ```bash npm install @ai-sdk/openai @ai-sdk/mcp @composio/core ai dotenv ``` ### 3. Set up environment variables Create a .env file in your project root. What's needed: - OPENAI_API_KEY: Your OpenAI API key for GPT model access - COMPOSIO_API_KEY: Your Composio API key for tool access - COMPOSIO_USER_ID: A unique identifier for the user session ```bash OPENAI_API_KEY=your_openai_api_key_here COMPOSIO_API_KEY=your_composio_api_key_here COMPOSIO_USER_ID=your_user_id_here ``` ### 4. Import required modules and validate environment What's happening: - We're importing all necessary libraries including Vercel AI SDK's OpenAI provider and Composio - The dotenv/config import automatically loads environment variables - The MCP client import enables connection to Composio's tool server ```typescript import "dotenv/config"; import { openai } from "@ai-sdk/openai"; import { Composio } from "@composio/core"; import * as readline from "readline"; import { streamText, type ModelMessage, stepCountIs } from "ai"; import { createMCPClient } from "@ai-sdk/mcp"; const composioAPIKey = process.env.COMPOSIO_API_KEY; const composioUserID = process.env.COMPOSIO_USER_ID; if (!process.env.OPENAI_API_KEY) throw new Error("OPENAI_API_KEY is not set"); if (!composioAPIKey) throw new Error("COMPOSIO_API_KEY is not set"); if (!composioUserID) throw new Error("COMPOSIO_USER_ID is not set"); const composio = new Composio({ apiKey: composioAPIKey, }); ``` ### 5. Create Tool Router session and initialize MCP client 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 mcp object contains the URL and authentication headers needed to connect to the MCP server - This session provides access to all Google Docs-related tools through the MCP protocol ```typescript async function main() { // Create a tool router session for the user const session = await composio.create(composioUserID!, { toolkits: ["googledocs"], }); const mcpUrl = session.mcp.url; ``` ### 6. Connect to MCP server and retrieve tools What's happening: - We're creating an MCP client that connects to our Composio Tool Router session via HTTP - The mcp.url provides the endpoint, and mcp.headers contains authentication credentials - The type: "http" is important - Composio requires HTTP transport - tools() retrieves all available Google Docs tools that the agent can use ```typescript const mcpClient = await createMCPClient({ transport: { type: "http", url: mcpUrl, headers: session.mcp.headers, // Authentication headers for the Composio MCP server }, }); const tools = await mcpClient.tools(); ``` ### 7. Initialize conversation and CLI interface What's happening: - We initialize an empty messages array to maintain conversation history - A readline interface is created to accept user input from the command line - Instructions are displayed to guide the user on how to interact with the agent ```typescript let messages: ModelMessage[] = []; console.log("Chat started! Type 'exit' or 'quit' to end the conversation.\n"); console.log( "Ask any questions related to googledocs, like summarize my last 5 emails, send an email, etc... :)))\n", ); const rl = readline.createInterface({ input: process.stdin, output: process.stdout, prompt: "> ", }); rl.prompt(); ``` ### 8. Handle user input and stream responses with real-time tool feedback What's happening: - We use streamText instead of generateText to stream responses in real-time - toolChoice: "auto" allows the model to decide when to use Google Docs tools - stopWhen: stepCountIs(10) allows up to 10 steps for complex multi-tool operations - onStepFinish callback displays which tools are being used in real-time - We iterate through the text stream to create a typewriter effect as the agent responds - The complete response is added to conversation history to maintain context - Errors are caught and displayed with helpful retry suggestions ```typescript 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; } messages.push({ role: "user", content: trimmedInput }); console.log("\nAgent is thinking...\n"); try { const stream = streamText({ model: openai("gpt-5"), messages, tools, toolChoice: "auto", stopWhen: stepCountIs(10), onStepFinish: (step) => { for (const toolCall of step.toolCalls) { console.log(`[Using tool: ${toolCall.toolName}]`); } if (step.toolCalls.length > 0) { console.log(""); // Add space after tool calls } }, }); for await (const chunk of stream.textStream) { process.stdout.write(chunk); } console.log("\n\n---\n"); // Get final result for message history const response = await stream.response; if (response?.messages?.length) { messages.push(...response.messages); } } catch (error) { console.error("\nAn error occurred while talking to the agent:"); console.error(error); console.log( "\nYou can try again or restart the app if it keeps happening.\n", ); } finally { rl.prompt(); } }); rl.on("close", async () => { await mcpClient.close(); console.log("\n👋 Session ended."); process.exit(0); }); } main().catch((err) => { console.error("Fatal error:", err); process.exit(1); }); ``` ## Complete Code ```typescript import "dotenv/config"; import { openai } from "@ai-sdk/openai"; import { Composio } from "@composio/core"; import * as readline from "readline"; import { streamText, type ModelMessage, stepCountIs } from "ai"; import { createMCPClient } from "@ai-sdk/mcp"; const composioAPIKey = process.env.COMPOSIO_API_KEY; const composioUserID = process.env.COMPOSIO_USER_ID; if (!process.env.OPENAI_API_KEY) throw new Error("OPENAI_API_KEY is not set"); if (!composioAPIKey) throw new Error("COMPOSIO_API_KEY is not set"); if (!composioUserID) throw new Error("COMPOSIO_USER_ID is not set"); const composio = new Composio({ apiKey: composioAPIKey, }); async function main() { // Create a tool router session for the user const session = await composio.create(composioUserID!, { toolkits: ["googledocs"], }); const mcpUrl = session.mcp.url; const mcpClient = await createMCPClient({ transport: { type: "http", url: mcpUrl, headers: session.mcp.headers, // Authentication headers for the Composio MCP server }, }); const tools = await mcpClient.tools(); let messages: ModelMessage[] = []; console.log("Chat started! Type 'exit' or 'quit' to end the conversation.\n"); console.log( "Ask any questions related to googledocs, like summarize my last 5 emails, send an email, etc... :)))\n", ); const rl = readline.createInterface({ input: process.stdin, output: process.stdout, prompt: "> ", }); 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; } messages.push({ role: "user", content: trimmedInput }); console.log("\nAgent is thinking...\n"); try { const stream = streamText({ model: openai("gpt-5"), messages, tools, toolChoice: "auto", stopWhen: stepCountIs(10), onStepFinish: (step) => { for (const toolCall of step.toolCalls) { console.log(`[Using tool: ${toolCall.toolName}]`); } if (step.toolCalls.length > 0) { console.log(""); // Add space after tool calls } }, }); for await (const chunk of stream.textStream) { process.stdout.write(chunk); } console.log("\n\n---\n"); // Get final result for message history const response = await stream.response; if (response?.messages?.length) { messages.push(...response.messages); } } catch (error) { console.error("\nAn error occurred while talking to the agent:"); console.error(error); console.log( "\nYou can try again or restart the app if it keeps happening.\n", ); } finally { rl.prompt(); } }); rl.on("close", async () => { await mcpClient.close(); console.log("\n👋 Session ended."); process.exit(0); }); } main().catch((err) => { console.error("Fatal error:", err); process.exit(1); }); ``` ## Conclusion You've successfully built a Google Docs agent using the Vercel AI SDK with streaming capabilities! This implementation provides a powerful foundation for building AI applications with natural language interfaces and real-time feedback. Key features of this implementation: - Real-time streaming responses for a better user experience with typewriter effect - Live tool execution feedback showing which tools are being used as the agent works - Dynamic tool loading through Composio's Tool Router with secure authentication - Multi-step tool execution with configurable step limits (up to 10 steps) - Comprehensive error handling for robust agent execution - Conversation history maintenance for context-aware responses You can extend this further by adding custom error handling, implementing specific business logic, or integrating additional Composio toolkits to create multi-app workflows. ## How to build Google Docs MCP Agent with another framework - [ChatGPT](https://composio.dev/toolkits/googledocs/framework/chatgpt) - [OpenAI Agents SDK](https://composio.dev/toolkits/googledocs/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/googledocs/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/googledocs/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/googledocs/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/googledocs/framework/codex) - [Cursor](https://composio.dev/toolkits/googledocs/framework/cursor) - [VS Code](https://composio.dev/toolkits/googledocs/framework/vscode) - [OpenCode](https://composio.dev/toolkits/googledocs/framework/opencode) - [OpenClaw](https://composio.dev/toolkits/googledocs/framework/openclaw) - [Hermes](https://composio.dev/toolkits/googledocs/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/googledocs/framework/cli) - [Google ADK](https://composio.dev/toolkits/googledocs/framework/google-adk) - [LangChain](https://composio.dev/toolkits/googledocs/framework/langchain) - [Mastra AI](https://composio.dev/toolkits/googledocs/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/googledocs/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/googledocs/framework/crew-ai) ## Related Toolkits - [Google Drive](https://composio.dev/toolkits/googledrive) - Google Drive is a cloud storage platform for uploading, sharing, and collaborating on files. It's perfect for keeping your documents accessible and organized across devices. - [Google Super](https://composio.dev/toolkits/googlesuper) - Google Super is an all-in-one suite combining Gmail, Drive, Calendar, Sheets, Analytics, and more. It gives you a unified platform to manage your digital life, boosting productivity and organization. - [Affinda](https://composio.dev/toolkits/affinda) - Affinda is an AI-powered document processing platform that automates data extraction from resumes, invoices, and more. It streamlines document-heavy workflows by turning files into structured, actionable data. - [Agility cms](https://composio.dev/toolkits/agility_cms) - Agility CMS is a headless content management system for building and managing digital experiences across platforms. It lets teams update content quickly and deliver omnichannel experiences with ease. - [Algodocs](https://composio.dev/toolkits/algodocs) - Algodocs is an AI-powered platform that automates data extraction from business documents. It delivers fast, secure, and accurate processing without templates or manual training. - [Api2pdf](https://composio.dev/toolkits/api2pdf) - Api2Pdf is a REST API for generating PDFs from HTML, URLs, and documents using powerful engines like wkhtmltopdf and Headless Chrome. It streamlines document conversion and automation for developers and businesses. - [Aryn](https://composio.dev/toolkits/aryn) - Aryn is an AI-powered platform for parsing, extracting, and analyzing data from unstructured documents. Use it to automate document processing and unlock actionable insights from your files. - [Boldsign](https://composio.dev/toolkits/boldsign) - Boldsign is a digital eSignature platform for sending, signing, and tracking documents online. Organizations use it to automate agreements and manage legally binding workflows efficiently. - [Boloforms](https://composio.dev/toolkits/boloforms) - BoloForms is an eSignature platform built for small businesses, offering unlimited signatures, templates, and forms. It simplifies digital document signing and team collaboration at a predictable, fixed price. - [Box](https://composio.dev/toolkits/box) - Box is a cloud content management and file sharing platform for businesses. It helps teams securely store, organize, and collaborate on files from anywhere. - [Carbone](https://composio.dev/toolkits/carbone) - Carbone is a blazing-fast report generator that turns JSON data into PDFs, Word docs, spreadsheets, and more using flexible templates. It lets you automate document creation at scale with minimal code. - [Castingwords](https://composio.dev/toolkits/castingwords) - CastingWords is a transcription service specializing in human-powered, accurate transcripts via a simple API. Get seamless audio-to-text conversion for interviews, meetings, podcasts, and more. - [Cloudconvert](https://composio.dev/toolkits/cloudconvert) - CloudConvert is a powerful file conversion service supporting over 200 file formats. It streamlines converting, compressing, and managing documents, media, and more, all in one place. - [Cloudlayer](https://composio.dev/toolkits/cloudlayer) - Cloudlayer is a document and asset generation service for creating PDFs and images via API or SDKs. It lets you automate high-quality doc creation, saving dev time and reducing manual work. - [Cloudpress](https://composio.dev/toolkits/cloudpress) - Cloudpress is a content export tool for Google Docs and Notion. It automates publishing to your favorite Content Management Systems. - [Contentful graphql](https://composio.dev/toolkits/contentful_graphql) - Contentful graphql is a content delivery API that lets you access Contentful data using GraphQL queries. It gives you efficient, flexible ways to fetch and manage structured content for any digital project. - [Conversion tools](https://composio.dev/toolkits/conversion_tools) - Conversion Tools is an online service for converting documents between formats such as PDF, Word, Excel, XML, and CSV. It lets you automate complex document workflows with just a few clicks. - [Convertapi](https://composio.dev/toolkits/convertapi) - ConvertAPI is a robust file conversion service for documents, images, and spreadsheets. It streamlines programmatic format changes and lets developers automate complex workflows with a single API. - [Craftmypdf](https://composio.dev/toolkits/craftmypdf) - CraftMyPDF is a web-based service for designing and generating PDFs with templates and live data. It streamlines document creation by automating personalized PDFs at scale. - [Docmosis](https://composio.dev/toolkits/docmosis) - Docmosis generates PDF and Word documents from user-defined templates. It's perfect for merging data fields to quickly produce reports, invoices, and business letters. ## Frequently Asked Questions ### 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 Vercel AI SDK v6? Yes, you can. Vercel AI SDK v6 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. --- [See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)