What are the prerequisites?
Python 3.11 or higher, a Gmail account, a Google Cloud Platform project with the Gmail API enabled, and the `uv` package installer.
@ykuchiki
Basic information
MCP server for Gmail API implemented in Python. Enables AI Agents to send, receive, search emails and manage labels in Gmail.
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"gmail-mcp-ykuchiki": {
"command": "uv",
"args": [
"init"
]
}
}
}Tool list not available yet
This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.
We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.
Gmail MCP is a server implementation that enables AI assistants to interact with Gmail through the Model Context Protocol (MCP). It provides tools for sending emails, managing drafts, reading emails, searching through your inbox, and managing Gmail labels. It uses OAuth2.0 authentication with the Gmail API.
Set up a Google Cloud Platform project with the Gmail API enabled, download OAuth credentials as credentials/client_secret_gmail_oauth.json, and install Python dependencies using uv. Then configure your MCP client to point to the server with uv run main.py. On first run, you will be prompted to authenticate with your Gmail account.
Python 3.11 or higher, a Gmail account, a Google Cloud Platform project with the Gmail API enabled, and the `uv` package installer.
Create a project in Google Cloud Console, enable the Gmail API, create OAuth credentials, download the JSON file, and save it as `credentials/client_secret_gmail_oauth.json` in the project root.
The server works with any MCP‑compatible client. Specific client integration instructions should be sought from the client’s official documentation.
The server uses OAuth 2.0. On first run, it prompts the user to authenticate with their Gmail account.
All dependencies are listed in `requirements.txt` and installed via `uv pip install -r requirements.txt`. The server is invoked using `uv run main.py`.
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