Enables access to Prometheus monitoring and time-series data through an MCP server, allowing AI assistants to query metrics, analyze performance data, and interact with Prometheus instances.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Prometheus MCP Servershow me the CPU usage for the last hour"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Prometheus MCP Server
A tool that allows access to Prometheus data through a Model Context Protocol server.
Installation
pipx install git+https://github.com/moohoorama/prometheus-mcp-server-py.gitRun Without Installation
You can also run the package directly without installing it using pipx run:
pipx run --spec git+https://github.com/moohoorama/prometheus-mcp-server-py.git prometheus-mcp --url http://your-prometheus-server:9090This is useful for testing or one-time usage scenarios.
Related MCP server: Prometheus MCP Server
Usage
# Command line arguments
prometheus-mcp --url http://your-prometheus-server:9090 \
--username username \
--password password
# Or
prometheus-mcp --url http://your-prometheus-server:9090 \
--token your-tokenCommand Line Arguments
--url: Prometheus server URL (required)--username: Username for basic authentication (optional)--password: Password for basic authentication (optional)--token: Token for authentication (optional)--org-id: Organization ID for multi-tenant setups (optional)
This server cannot be installed
Resources
Looking for Admin?
Admins can modify the Dockerfile, update the server description, and track usage metrics. If you are the server author, to access the admin panel.