Generic MCP Server for Google Workspace
Enables AI agents to send emails, create drafts in Gmail, and append content to Google Docs via standardized MCP tools.
README
Generic MCP Server for Google Workspace
A Model Context Protocol (MCP) server that securely exposes Google Workspace capabilities to AI Agents (like Claude Desktop, OpenAI, or Cursor) through standardized MCP tools.
This server acts as a bridge, allowing any MCP-compatible AI client to interact with Google APIs without requiring custom integrations inside the agent itself.
Features & Tools
Currently, the server exposes the following tools:
gmail_send_email: Sends an email (supports To, Cc, Bcc, Subject, and Text/HTML bodies).gmail_create_draft: Creates an email draft in the authenticated user's account.gdocs_append_content: Appends text to the end of a specific Google Document (requires the Document ID).
Prerequisites
- Node.js (v18 or newer)
- Google Cloud Console Project:
- Enable the Gmail API and Google Docs API.
- Create an OAuth 2.0 Client ID (Web application).
- Set the Authorized Redirect URI to
http://localhost(or your domain).
Setup & Local Authentication
-
Install Dependencies
npm install -
Configure Environment Variables Copy
.env.exampleto.envand add your Google credentials:GOOGLE_CLIENT_ID=your_client_id_here GOOGLE_CLIENT_SECRET=your_client_secret_here GOOGLE_REDIRECT_URI=http://localhost -
Generate OAuth Tokens To grant the server access to your Google account, you must complete the OAuth flow once. Run the token generation script:
npm run build node dist/auth/generate_token.jsFollow the on-screen instructions. The script will save your access and refresh tokens locally in
.tokens.json.
Running the Server
Local Development
To run the server locally, you can use the standard build and start scripts:
npm run build
npm start
Note: The server is configured to run over HTTP using Server-Sent Events (SSE) by default on http://localhost:3000/sse.
Cloud Deployment (Railway)
This server is pre-configured to be easily deployable to cloud services like Railway.
When deploying to a remote host:
- Ensure the
TOKEN_PATHenvironment variable is set to a persistent volume (e.g.,/app/data/.tokens.json), as the local file system in most cloud providers is ephemeral. - The server will automatically bind to the
PORTenvironment variable provided by your cloud host.
For full instructions, see the Deployment Plan.
Connecting an AI Agent
To connect an AI Agent to this MCP Server, add the HTTP URL to your agent's MCP configuration file (e.g., in Claude Desktop).
{
"mcpServers": {
"google-workspace": {
"url": "http://localhost:3000/sse"
}
}
}
(If deployed remotely, replace the URL with your remote domain, e.g., https://my-server.up.railway.app/sse).
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.