CaesarYangs_prometheus_mcp_server
The MCP Server for Prometheus is a dedicated Model Context Protocol server designed to retrieve and analyze data from Prometheus databases, enabling complex metric analysis and querying. It supports Large Language Models in accessing extensive metrics for in-depth data exploration.
MCP Server for Prometheus
A Model Context Protocol (MCP) server for retrieving data from Prometheus databases. This MCP server enables Large Language Models (LLMs) to invoke tool functions that retrieve and analyze vast amounts of metric data, search metric usage, execute complex queries, and perform other related tasks through pre-defined routes.
- Data Retrieval: Fetch specific metrics or ranges of data from Prometheus.
- Metric Analysis: Perform statistical analysis on retrieved metrics.
- Usage Search: Find and explore metric usage patterns.
- Complex Querying: Execute advanced PromQL queries for in-depth data exploration.
Capabilities
- Retrieve comprehensive metric information from Prometheus
- Fetch and analyze specific metric data
- Analyze metric data within custom time ranges
- Planned features: data filtering and matching using specific labels
Getting Started
To run the MCP, prepare a Python virtual environment (venv), install all required packages, and activate the environment. After setting up, the MCP server can be started using various methods.
Usage
With MCP Client
Configure Claude Desktop app and connect it to this MCP server using specified configuration.
Standalone MCP Server
Start the MCP server independently using the command line.
Contributing
Contributions are welcome! Fork the repo, create a branch, commit changes, push the branch, and open a Pull Request. For major changes, discuss them by opening an issue first.
License
MIT License
References & Acknowledgments
Inspired by Prometheus API Client and MySQL MCP Server implementations.