MCP Server for Prometheus
About
MCP Server for Prometheus is a Model Context Protocol server that lets Large Language Models retrieve and analyze metric data from Prometheus databases. It provides pre‑defined tool functions for fetching metrics, performing analysis, searching usage patterns, and executing…
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- Retrieve metric names and descriptions from Prometheus
- Fetch and analyze specific metric data by name
- Analyze metric data within custom time ranges
- Execute advanced PromQL queries for in‑depth exploration
Setting up with Highlight
This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:
- Download and install Highlight from highlightai.com/download
- Navigate to the plugins tab and select "Add Custom Plugin"
-
Configure the plugin with the settings below
Plugin Name
MCP Server for PrometheusCommand (node, npx, python, etc.)Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.
- Enable "Start Automatically" if you want the plugin to start when Highlight launches
From the repository
Create a Python virtual environment, install the required packages from requirements.txt, and set the PROMETHEUS_HOST environment variable (default http://localhost:9090). You can then run server.py either as a standalone server (using uv or python3) or configure it in Claude Desktop by adding the server entry to claude_desktop_config.json.
Claude Desktop / Cursor
Paste into your MCP client config file to install this server.
{
"mcpServers": {
"mcp server for prometheus": {
"CaesarYangs_prometheus_mcp_server": {
"command": "python3",
"args": [
"-m",
"venv",
".venv"
]
}
}
}
}McpServers
{
"CaesarYangs_prometheus_mcp_server": {
"command": "python3",
"args": [
"-m",
"venv",
".venv"
]
}
}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 with enhanced control over usage.
- 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.
Capibilites
✅ Retrieve comprehensive metric information, including names and descriptions, from Prometheus
✅ Fetch and analyze specific metric data using metric names
✅ Analyze metric data within custom time ranges
🚧 Filter and match data using specific labels (in development)
⏳ Additional features planned...
Getting Started
MCP runing requires a python virtual environment(venv), all packages should be installed into this venv so the MCP server can be automically started.
Prepare python env
cd ./src/prometheus_mcp_server
python3 -m venv .venv
```sh
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