Google Workspace MCP Server
Provides tools to create draft emails and send emails directly from a Gmail account.
Provides a tool to append text content to the end of a specified Google Document.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Google Workspace MCP ServerSend an email to john@example.com about the project update"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Google Workspace MCP Server (Railway Deployment)
A robust, generic Model Context Protocol (MCP) Server that integrates AI agents with Google Workspace. It acts as a bridge, enabling any standard MCP-compliant AI agent (such as Claude Desktop) to securely interact with Gmail and Google Docs.
This version has been optimized for deployment to cloud providers like Railway using an Express-based HTTP server with Server-Sent Events (SSE) and API Key authentication.
Provided Tools
gmail_draft_email: Creates a draft email in your Gmail account without sending it.gmail_send_email: Sends an email directly from your Gmail account.docs_append_content: Appends text content to the end of a specified Google Document.
Related MCP server: gg-mcp
Setup Instructions
1. Configure Environment Variables
This server expects the following environment variables to securely connect to Google APIs without relying on local files:
PORT: (Optional) Port for the Express server (default: 3000). Provided automatically by Railway.MCP_API_KEY: A secure random string you choose to protect your endpoint (e.g.,sk-mcp-12345...).GOOGLE_CLIENT_ID: Your Google OAuth 2.0 Client ID.GOOGLE_CLIENT_SECRET: Your Google OAuth 2.0 Client Secret.GOOGLE_REFRESH_TOKEN: The refresh token generated after your initial OAuth consent flow.
2. Deploy to Railway
Push this repository to GitHub.
Create a new project in Railway and select the repository.
Railway will automatically build the TypeScript project via
npm run buildand start it.Add the required environment variables in the Railway dashboard.
Generate a public domain for your Railway service (e.g.,
https://my-mcp-server.up.railway.app).
3. Configure Your MCP Client
Instead of running a local node process, you must configure your AI agent to connect via SSE over HTTP. Provide the API key in the environment to authenticate.
Claude Desktop Configuration
Add this server to your claude_desktop_config.json:
{
"mcpServers": {
"google-workspace": {
"command": "npx",
"args": ["-y", "@modelcontextprotocol/inspector", "http://my-mcp-server.up.railway.app/sse"],
"env": {
"MCP_API_KEY": "your_secure_api_key_here"
}
}
}
}(Note: To connect Claude Desktop directly to a remote SSE server, you typically use a specialized SSE client wrapper, or pass the authorization header via the client's built-in HTTP connector if supported).
This server cannot be installed
Maintenance
Resources
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Looking for Admin?
If you are the server author, to access and configure the admin panel.
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