Prometheus MCP Server is a specialized Model Context Protocol (MCP) server designed to provide standardized access to Prometheus metrics and queries. It enables AI assistants to interact with Prometheus by executing PromQL queries and analyzing metrics data through a unified interface. The server supports key features such as executing instant and range PromQL queries, discovering and exploring available metrics, and retrieving metadata for specific metrics. It also supports authentication mechanisms including basic authentication and bearer token authentication, configurable via environment variables. The server is containerized using Docker, facilitating easy deployment and integration into various environments. The project is structured with a clear source directory containing the MCP server implementation and main application logic. It includes comprehensive testing to ensure reliability and robustness, covering configuration validation, server functionality, error handling, and main application logic. The server offers configurable interactive tools for AI assistants, allowing customization of available functionalities to optimize context window usage. Usage involves configuring environment variables to connect to a Prometheus server, optionally setting authentication credentials, and running the server via Docker. The server supports multi-tenant setups such as Cortex, Mimir, or Thanos by allowing organization ID configuration. The project encourages contributions and provides detailed instructions for development, dependency management, and testing. Overall, Prometheus MCP Server bridges Prometheus monitoring systems with AI-driven analysis by leveraging the Model Context Protocol, enhancing the ability of AI assistants to query, explore, and interpret Prometheus metrics efficiently and securely.
https://github.com/pab1it0/prometheus-mcp-server
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