MCP server for Prometheus integration
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# Prometheus MCP Server A [Model Context Protocol][mcp] (MCP) server for Prometheus. This provides access to your Prometheus metrics and queries through standardized MCP interfaces, allowing AI assistants to execute PromQL queries and analyze your metrics data. <a href="https://glama.ai/mcp/servers/@pab1it0/prometheus-mcp-server"> <img width="380" height="200" src="https://glama.ai/mcp/servers/@pab1it0/prometheus-mcp-server/badge" alt="Prometheus Server MCP server" /> </a> [mcp]: https://modelcontextprotocol.io ## Quick Start ### 🚀 **For End Users (PyPI)** ```bash # Install and run in one command uvx --from raihan0824-prometheus-mcp-server prometheus-mcp-server ``` ### 🛠️ **For Developers (Local)** ```bash # Clone and install in development mode git clone https://github.com/raihan0824/prometheus-mcp-server.git cd prometheus-mcp-server uv pip install -e . prometheus-mcp-server ``` ## Features - [x] Execute PromQL queries against Prometheus - [x] Discover and explore metrics - [x] List available metrics - [x] Get metadata for specific metrics - [x] View instant query results - [x] View range query results with different step intervals - [x] Authentication support - [x] Basic auth from environment variables - [x] Bearer token auth from environment variables - [x] Docker containerization support - [x] Provide interactive tools for AI assistants The list of tools is configurable, so you can choose which tools you want to make available to the MCP client. This is useful if you don't use certain functionality or if you don't want to take up too much of the context window. ## Installation ### Option 1: Install from PyPI (Recommended for Users) ```bash # Using uvx (recommended for Claude Desktop) uvx --from raihan0824-prometheus-mcp-server prometheus-mcp-server # Using pip pip install raihan0824-prometheus-mcp-server # Using uv uv add raihan0824-prometheus-mcp-server ``` ### Option 2: Install from Source (For Development) ```bash # Clone th…
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