What is the Gmail MCP Server?
It is an MCP server that gives LLMs like Claude the ability to interact with Gmail – listing, searching, reading, sending, and replying to emails.
@Imsharad
基本信息
A Gmail Model Context Protocol server for seamless integration with AI assistants
使用下面的配置,将此服务器添加到你的 MCP 客户端。
{
"mcpServers": {
"gmail": {
"command": "python",
"args": [
"-m",
"src.server"
],
"cwd": "/path/to/gmail-mcp-server"
}
}
}工具列表暂未提供
当前收录暂时没有可展示的工具列表,不代表服务没有工具。请查阅项目文档了解支持的能力。
工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。
The Gmail MCP Server provides access to Gmail functionality through the Model Context Protocol, allowing LLMs like Claude to interact with your email. It is designed for developers and AI assistants that need to read, search, send, and reply to emails programmatically.
Set up a Python virtual environment, install dependencies, enable the Gmail API in Google Cloud Console, and download OAuth 2.0 credentials as credentials.json. Run the server with python -m src.server; the first launch opens a browser for authentication. Afterwards, configure Claude Desktop by adding the server to claude_desktop_config.json with the command python -m src.server and the project directory as the working directory.
It is an MCP server that gives LLMs like Claude the ability to interact with Gmail – listing, searching, reading, sending, and replying to emails.
Create a Google Cloud project, enable the Gmail API, and generate OAuth 2.0 credentials (desktop application type). Download the credentials as `credentials.json` into the project root. On first run, the server opens a browser for authorization and saves the tokens to `token.json`.
Keep your `credentials.json` and `token.json` files secure and never commit them to version control. If you suspect compromise, revoke the credentials in the Google Cloud Console and generate new ones.
The Gmail API allows up to 1,000,000,000 quota units per day, with each API method consuming different amounts. For details, refer to Google’s Gmail API Quotas documentation.
Add the server to your `claude_desktop_config.json` with the command `python -m src.server` and set the working directory to the project path.

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