google_workspace_mcp

See it in action:

A quick plug for AI-Enhanced Docs

This README was crafted with AI assistance, and here's why that matters

As a solo developer building open source tools that may only ever serve my own needs, comprehensive documentation often wouldn't happen without AI help. Using agentic dev tools like Roo & Claude Code that understand the entire codebase, AI doesn't just regurgitate generic content - it extracts real implementation details and creates accurate, specific documentation.

In this case, Sonnet 4 took a pass & a human (me) verified them 6/28/25.

🌐 Overview

A production-ready MCP server that integrates all major Google Workspace services with AI assistants. Built with FastMCP for optimal performance, featuring advanced authentication handling, service caching, and streamlined development patterns.

✨ Features

• 🔐 Advanced OAuth 2.0: Secure authentication with automatic token refresh, transport-aware callback handling, session management, and centralized scope management
• 📅 Google Calendar: Full calendar management with event CRUD operations
• 📁 Google Drive: File operations with native Microsoft Office format support (.docx, .xlsx)
• 📧 Gmail: Complete email management with search, send, and draft capabilities
• 📄 Google Docs: Document operations including content extraction, creation, and comment management
• 📊 Google Sheets: Comprehensive spreadsheet management with flexible cell operations and comment management
• 🖼️ Google Slides: Presentation management with slide creation, updates, content manipulation, and comment management
• 📝 Google Forms: Form creation, retrieval, publish settings, and response management
• 💬 Google Chat: Space management and messaging capabilities
• 🔄 Multiple Transports: HTTP with SSE fallback, OpenAPI compatibility via mcpo
• ⚡ High Performance: Service caching, thread-safe sessions, FastMCP integration
• 🧩 Developer Friendly: Minimal boilerplate, automatic service injection, centralized configuration

🚀 Quick Start

Simplest Start (uvx - Recommended)

Run instantly without manual installation - you must configure OAuth credentials when using uvx. You can use either environment variables (recommended for production) or set the GOOGLE_CLIENT_SECRET_PATH (or legacy GOOGLE_CLIENT_SECRETS) environment variable to point to your client_secret.json file.

# Set OAuth credentials via environment variables (recommended)
export GOOGLE_OAUTH_CLIENT_ID="your-client-id.apps.googleusercontent.com"
export GOOGLE_OAUTH_CLIENT_SECRET="your-client-secret"

# Start the server with all Google Workspace tools
uvx workspace-mcp

# Start with specific tools only
uvx workspace-mcp --tools gmail drive calendar

# Start in HTTP mode for debugging
uvx workspace-mcp --transport streamable-http

Requires Python 3.11+ and uvx. The package is available on PyPI.

Development Installation

For development or customization:

git clone https://github.com/taylorwilsdon/google_workspace_mcp.git
cd google_workspace_mcp
uv run main.py

Prerequisites

• Python 3.11+
• uvx (for instant installation) or uv (for development)
• Google Cloud Project with OAuth 2.0 credentials

Configuration

1. Google Cloud Setup:

   • Create OAuth 2.0 credentials (web application) in Google Cloud Console

   • Enable APIs: Calendar, Drive, Gmail, Docs, Sheets, Slides, Forms, Chat

   • Add redirect URI: http://localhost:8000/oauth2callback

   • Configure credentials using one of these methods:

     Option A: Environment Variables (Recommended for Production)

     export GOOGLE_OAUTH_CLIENT_ID="your-client-id.apps.googleusercontent.com"
     export GOOGLE_OAUTH_CLIENT_SECRET="your-client-secret"
     export GOOGLE_OAUTH_REDIRECT_URI="http://localhost:8000/oauth2callback"  # Optional
     

     Option B: File-based (Traditional)

     • Download credentials as client_secret.json in project root
     • To use a different location, set GOOGLE_CLIENT_SECRET_PATH (or legacy GOOGLE_CLIENT_SECRETS) environment variable with the file path

   Credential Loading Priority:

   1. Environment variables (GOOGLE_OAUTH_CLIENT_ID, GOOGLE_OAUTH_CLIENT_SECRET)
   2. File specified by GOOGLE_CLIENT_SECRET_PATH or GOOGLE_CLIENT_SECRETS environment variable
   3. Default file (client_secret.json in project root)

   Why Environment Variables?

   • ✅ Containerized deployments (Docker, Kubernetes)
   • ✅ Cloud platforms (Heroku, Railway, etc.)
   • ✅ CI/CD pipelines
   • ✅ No secrets in version control
   • ✅ Easy credential rotation

2. Environment:

   export OAUTHLIB_INSECURE_TRANSPORT=1  # Development only
   export USER_GOOGLE_EMAIL=your.email@gmail.com  # Optional: Default email for auth - use this for single user setups and you won't need to set your email in system prompt for magic auth
   

3. Server Configuration: The server's base URL and port can be customized using environment variables:

   • WORKSPACE_MCP_BASE_URI: Sets the base URI for the server (default: http://localhost). This affects the server_url used for Gemini native function calling and the OAUTH_REDIRECT_URI.
   • WORKSPACE_MCP_PORT: Sets the port the server listens on (default: 8000). This affects the server_url, port, and OAUTH_REDIRECT_URI.
   • USER_GOOGLE_EMAIL: Optional default email for authentication flows. If set, the LLM won't need to specify your email when calling start_google_auth.

Start the Server

# Default (stdio mode for MCP clients)
uv run main.py

# HTTP mode (for web interfaces and debugging)
uv run main.py --transport streamable-http

# Single-user mode (simplified authentication)
uv run main.py --single-user

# Selective tool registration (only register specific tools)
uv run main.py --tools gmail drive calendar
uv run main.py --tools sheets docs
uv run main.py --single-user --tools gmail  # Can combine with other flags

# Docker
docker build -t workspace-mcp .
docker run -p 8000:8000 -v $(pwd):/app workspace-mcp --transport streamable-http

Available Tools for --tools flag: gmail, drive, calendar, docs, sheets, forms, chat

Connect to Claude Desktop

The server supports two transport modes:

Stdio Mode (Default - Recommended for Claude Desktop)

Option 1: Auto-install (Recommended)

python install_claude.py

Option 2: Manual Configuration

1. Open Claude Desktop Settings → Developer → Edit Config
2. This creates/opens the config file at:
   • macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
   • Windows: %APPDATA%\Claude\claude_desktop_config.json
3. Add the server configuration:

{
  "mcpServers": {
    "google_workspace": {
      "command": "uvx",
      "args": ["workspace-mcp"],
      "env": {
        "GOOGLE_OAUTH_CLIENT_ID": "your-client-id.apps.googleusercontent.com",
        "GOOGLE_OAUTH_CLIENT_SECRET": "your-client-secret"
      }
    }
  }
}

Alternative (Development Installation):

{
  "mcpServers": {
    "google_workspace": {
      "command": "uv",
      "args": ["run", "main.py"],
      "cwd": "/path/to/google_workspace_mcp",
      "env": {
        "GOOGLE_OAUTH_CLIENT_ID": "your-client-id.apps.googleusercontent.com",
        "GOOGLE_OAUTH_CLIENT_SECRET": "your-client-secret"
      }
    }
  }
}

HTTP Mode (For debugging or web interfaces)

If you need to use HTTP mode with Claude Desktop:

{
  "mcpServers": {
    "google_workspace": {
      "command": "npx",
      "args": ["mcp-remote", "http://localhost:8000/mcp"]
    }
  }
}

Note: Make sure to start the server with --transport streamable-http when using HTTP mode.

First-Time Authentication

The server features transport-aware OAuth callback handling:

• Stdio Mode: Automatically starts a minimal HTTP server on port 8000 for OAuth callbacks
• HTTP Mode: Uses the existing FastAPI server for OAuth callbacks
• Same OAuth Flow: Both modes use http://localhost:8000/oauth2callback for consistency

When calling a tool:

1. Server returns authorization URL
2. Open URL in browser and authorize
3. Server handles OAuth callback automatically (on port 8000 in both modes)
4. Retry the original request

🧰 Available Tools

Note: All tools support automatic authentication via @require_google_service() decorators with 30-minute service caching.

📅 Google Calendar ()

📁 Google Drive ()

📧 Gmail ()

📝 Google Docs ()

📊 Google Sheets ()

🖼️ Google Slides ()

📝 Google Forms ()

💬 Google Chat ()

🛠️ Development

Project Structure

google_workspace_mcp/
├── auth/              # Authentication system with decorators
├── core/              # MCP server and utilities
├── g{service}/        # Service-specific tools
├── main.py            # Server entry point
├── client_secret.json # OAuth credentials (not committed)
└── pyproject.toml     # Dependencies

Adding New Tools

from auth.service_decorator import require_google_service

@require_google_service("drive", "drive_read")  # Service + scope group
async def your_new_tool(service, param1: str, param2: int = 10):
    """Tool description"""
    # service is automatically injected and cached
    result = service.files().list().execute()
    return result  # Return native Python objects

Architecture Highlights

• Service Caching: 30-minute TTL reduces authentication overhead
• Scope Management: Centralized in SCOPE_GROUPS for easy maintenance
• Error Handling: Native exceptions instead of manual error construction
• Multi-Service Support: @require_multiple_services() for complex tools

🔒 Security

• Credentials: Never commit client_secret.json or .credentials/ directory
• OAuth Callback: Uses http://localhost:8000/oauth2callback for development (requires OAUTHLIB_INSECURE_TRANSPORT=1)
• Transport-Aware Callbacks: Stdio mode starts a minimal HTTP server only for OAuth, ensuring callbacks work in all modes
• Production: Use HTTPS for callback URIs and configure accordingly
• Network Exposure: Consider authentication when using mcpo over networks
• Scope Minimization: Tools request only necessary permissions

🌐 Integration with Open WebUI

To use this server as a tool provider within Open WebUI:

1. Create MCPO Configuration

Create a file named config.json with the following structure to have mcpo make the streamable HTTP endpoint available as an OpenAPI spec tool:

{
  "mcpServers": {
    "google_workspace": {
      "type": "streamablehttp",
      "url": "http://localhost:8000/mcp"
    }
  }
}

2. Start the MCPO Server

mcpo --port 8001 --config config.json --api-key "your-optional-secret-key"

This command starts the mcpo proxy, serving your active (assuming port 8000) Google Workspace MCP on port 8001.

3. Configure Open WebUI

1. Navigate to your Open WebUI settings
2. Go to "Connections" → "Tools"
3. Click "Add Tool"
4. Enter the Server URL: http://localhost:8001/google_workspace (matching the mcpo base URL and server name from config.json)
5. If you used an --api-key with mcpo, enter it as the API Key
6. Save the configuration

The Google Workspace tools should now be available when interacting with models in Open WebUI.

📄 License

MIT License - see LICENSE file for details.