What are the runtime requirements?
Python 3.13+ and a Google Cloud project with the Google Chat API and People API (for user display names) enabled.
@chy168
Basic information
No overview available yet
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"google-chat-mcp-server": {
"command": "uv",
"args": [
"run",
"python",
"server.py",
"--auth",
"cli"
]
}
}
}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.
Introduction is a Google Chat integration for MCP (Model Control Protocol) servers, written in Python with FastMCP. It provides tools to access and interact with Google Chat spaces and messages, and includes a separate authentication server for OAuth2 login. It is intended for developers who want to connect AI assistants or other MCP clients to Google Chat.
Clone the repository, set up a Google Cloud project with the Chat and People APIs enabled, and download OAuth2 credentials as credentials.json. Then choose an authentication mode: run uv run python server.py --auth cli for headless environments (paste a redirect URL), or uv run python server.py --auth web --port 8000 for environments with a local browser. After obtaining a token, configure your MCP client with a uv command pointing to server.py and the token path, or use the provided Docker/Podman container.
Python 3.13+ and a Google Cloud project with the Google Chat API and People API (for user display names) enabled.
Two modes are available: **CLI mode** (recommended for headless environments) displays an authorization URL that you open in any browser, then you paste the redirect URL back into the terminal. **Web mode** runs a local web server on port 8000 and opens the authorization page in the local browser. Both modes save a `token.json` file.
`get_chat_spaces()` lists all accessible spaces, and `get_space_messages(space_name, start_date, end_date)` retrieves messages from a specific space with optional date filtering.
Yes. Docker and Podman images are available. Mount your project directory (containing `token.json`) to `/data` and pass `--token-path=/data/token.json`. For the auth server in web mode, also map port 8000.
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