@KishoreKu
Basic information
Self-healing MCP server for Google Cloud.
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"gcp-manager": {
"command": "python",
"args": [
"/path/to/mcp-server-gcp-manager/server.py"
],
"env": {
"GCLOUD_PATH": "/path/to/your/gcloud"
}
}
}
}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.
Mcp Server Gcp Manager is an open-source Model Context Protocol (MCP) server that enables AI agents (such as Claude, Llama 3.1, or custom LangChain bots) to interact with Google Cloud Platform safely and autonomously. It bridges an LLM with the gcloud CLI, allowing natural‑language management of Cloud Run services and Google Secret Manager.
Installation requires Python 3.10+, a working gcloud installation authenticated with a project, and the mcp Python package. Optionally set the GCLOUD_PATH environment variable if gcloud is not auto‑detected. For Claude Desktop, add a gcp-manager entry to claude_desktop_config.json. For LangChain or custom agents, use langchain-mcp-adapters to connect to the server via stdio transport.
Python 3.10 or later, and the Google Cloud SDK (`gcloud`) installed and authenticated. On macOS, install via `brew install --cask google-cloud-sdk`. Authenticate with `gcloud auth login` and set your project with `gcloud config set project [YOUR_PROJECT_ID]`.
The server auto‑detects gcloud. If it fails, set the environment variable `GCLOUD_PATH` to the full path of the gcloud executable (e.g., `/usr/local/bin/gcloud` on Mac/Linux or the Windows equivalent).
Add a `gcp-manager` entry to your `claude_desktop_config.json` specifying the Python interpreter and the path to `server.py`. Example: `"command": "/path/to/venv/bin/python", "args": ["/path/to/mcp-gcp-manager/server.py"]`.
Three tools: `list_running_services` (list Cloud Run services), `create_secret` (create/update secrets, auto‑enabling Secret Manager API), and `deploy_service` (deploy new revisions with memory/image updates).
Clone the repository, create a Python virtual environment, activate it, and run `pip install mcp`.
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