Prometheus
Enables Large Language Models (LLMs) to interact programmatically with Prometheus instances.
About
The Prometheus server acts as a Model Context Protocol (MCP) server, bridging LLMs with a running Prometheus instance. This integration allows AI models to perform a variety of operations, including dynamically generating and executing PromQL queries, listing and analyzing metrics, retrieving configuration and runtime information, and managing alerts and rules. It empowers LLMs to directly leverage Prometheus's robust monitoring capabilities, facilitating advanced automated analysis and interaction with time-series data.
Key Features
- 12 GitHub stars
- Optionally enable dangerous TSDB administrative functions like data deletion and snapshot creation.
- Execute instant and range PromQL queries against Prometheus.
- Retrieve comprehensive Prometheus metric metadata, labels, and target information.
- Access Prometheus runtime, build, and TSDB usage statistics.
- List and analyze active Prometheus alerts and recording rules.
Use Cases
- Automated troubleshooting and analysis of Prometheus metrics via LLM commands.
- LLM-driven exploration and querying of Prometheus monitoring data.
- Integrating Prometheus observability into AI-powered operational tools.