About Enhanced Gmail MCP Server
Enhanced Gmail MCP Server is a Python MCP server that lets Claude and other AI assistants manage Gmail through natural language. It covers sending and reading mail, drafts, labels, folders, search, filters and archiving. Setup requires a Google Cloud project with the Gmail API enabled and OAuth 2.0 credentials.
Key features
- 01Send, read, trash and mark emails as read
- 02Create, list and edit draft emails
- 03Create, apply, rename and delete labels and folders
- 04Search with Gmail query syntax and manage filters
- 05Archive, batch archive and restore emails to inbox
Use cases
- 01Ask an AI assistant to list unread emails and organize labels
- 02Batch archive messages from a specific newsletter sender
- 03Draft meeting-related emails from natural language prompts
MCP support
This is an MCP server that exposes Gmail mail, label, filter and archive operations as tools to MCP clients, authenticating to the Gmail API with OAuth 2.0.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.
Tools
Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.
Details
From the project READMEEnhanced Gmail MCP Server
A powerful and feature-rich Model Context Protocol (MCP) server for Gmail integration, written in Python. This server enables AI assistants like Claude to interact with Gmail through natural language, providing comprehensive email management capabilities.
🌟 Key Features
📧 Complete Email Management
- Send emails with customizable subject, content, and recipients
- Read and retrieve email content with full metadata
- Move emails to trash with confirmation
- Mark emails as read/unread
- Open emails directly in browser
📝 Draft Management
- Create draft emails for later review
- List all draft emails
- Edit existing drafts
🏷️ Advanced Label Management
- List all available labels
- Create custom labels
- Apply/remove labels from emails
- Rename existing labels
- Delete unused labels
- Search emails by label
📁 Folder Organization
- Create new folders (implemented as Gmail labels)
- Move emails between folders
- List all available folders
🔍 Powerful Search & Filtering
- Search emails using Gmail's advanced query syntax
- Create, manage, and delete email filters
- Filter by sender, recipient, subject, content, and more
- Customize search results with flexible parameters
🗄️ Archive Management
- Archive emails (remove from inbox without deleting)
- Batch archive multiple emails matching search criteria
- List all archived emails
- Restore archived emails to inbox
🚀 Getting Started
Prerequisites
- Python 3.12+
- Python MCP SDK >= 2.0
- Google Cloud project with Gmail API enabled
- OAuth 2.0 credentials
Installation
# Clone the repository
git clone https://github.com/theposch/gmail-mcp.git
cd gmail-mcp
# Set up a virtual environment
python -m venv .venv
source .venv/bin/activate # On Windows: .venv\Scripts\activate
# Install the package
pip install -e .
Google Cloud Setup
- Create a new Google Cloud project
- Enable the Gmail API
- Configure the OAuth consent screen:
- Select "External" user type
- Add your email as a test user
- Add the scope:
https://www.googleapis.com/auth/gmail/modify
- Create OAuth 2.0 credentials:
- Choose "Desktop app" as the application type
- Download the JSON credentials file
Configuration
Store your credentials securely and specify their location when running the server:
# Example directory structure for credentials
mkdir -p ~/.gmail-mcp
# Move your downloaded credentials file
mv ~/Downloads/client_secret_*.json ~/.gmail-mcp/credentials.json
🔧 Usage
Running with Claude Desktop
Add the following to your Claude Desktop configuration file (typically at ~/Library/Application Support/Claude/claude_desktop_config.json):
{
"mcpServers": {
"gmail": {
"command": "uv",
"args": [
"--directory",
"/absolute/path/to/gmail-mcp",
"run",
"gmail",
"--creds-file-path",
"/absolute/path/to/credentials.json",
"--token-path",
"/absolute/path/to/tokens.json"
]
}
}
}
Testing with MCP Inspector
For testing and debugging, use the MCP Inspector:
npx @modelcontextprotocol/inspector uv run /path/to/gmail-mcp/src/gmail/server.py --creds-file-path /path/to/credentials.json --token-path /path/to/tokens.json
🔐 Security Considerations
- Never commit credentials or token files to version control
- Store credentials in a secure location with appropriate permissions
- The server will request user confirmation before performing sensitive actions
- Review Google Cloud Console regularly for unusual activity
- Consider using environment variables for sensitive paths
🛠️ Architecture
This implementation features a comprehensive single-file architecture that handles all Gmail operations through the Google API client libraries. Key components include:
- OAuth2 authentication with automatic token refresh
- Comprehensive error handling and logging
- Structured tool definitions with clear input schemas
- Efficient email parsing and formatting
📚 Example Prompts
Try these prompts with Claude after connecting the Gmail MCP server:
- "Show me my unread emails"
- "Search for emails from [email protected] with attachments"
- "Create a new label called 'Important Projects'"
- "Draft an email to [email protected] about the upcoming meeting"
- "Archive all emails from [email protected]"
- "Create a filter to automatically label emails from my team"
🤝 Contributing
Contributions are welcome! Please feel free to submit a Pull Request.
- Fork the repository
- Create your feature branch (
git checkout -b feature/amazing-feature) - Commit your changes (
git commit -m 'Add some amazing feature') - Push to the branch (
git push origin feature/amazing-feature) - Open a Pull Request
📄 License
This project is licensed under the GPL-3.0 License - see the LICENSE file for details.
🙏 Acknowledgments
- Inspired by various MCP server implementations in the community
- Built with the Model Context Protocol framework
- Uses Google's official API client libraries
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.