Prometheus MCP
P

Prometheus MCP

Prometheus MCP Server is a protocol server that enables seamless docking between AI assistants and the Prometheus monitoring system. It supports querying, analyzing, and discovering monitoring metrics in natural language and is compatible with multiple development tool clients.
2.5 points
8.5K

What is Prometheus MCP Server?

Prometheus MCP Server is a middleware that enables your AI assistants (such as VS Code Copilot, Cursor AI, etc.) to directly interact with the Prometheus monitoring system. Through natural language instructions, you can query metrics and analyze data without writing complex PromQL query statements.

How to use Prometheus MCP Server?

Simply add the MCP server settings to your AI client configuration and specify the Prometheus address. After installation, you can directly ask for monitoring data in natural language, such as 'Show CPU usage' or 'Compare the error rates between production and test environments'.

Applicable scenarios

It is suitable for scenarios where developers and operations personnel need to quickly query monitoring metrics, analyze system performance, and troubleshoot problems. It is especially suitable for users who need to frequently interact with the monitoring system but do not want to memorize complex query syntax.

Main features

Metric discovery
Browse and explore all available metrics and labels in Prometheus
Natural language query
Query monitoring data in simple English without writing PromQL
Trend analysis
Get the change trends and comparisons of metrics within a time range
Multi - client support
Supports multiple AI clients such as VS Code, Cursor, Windsurf, and Claude Desktop
Advantages
Query monitoring data without learning PromQL
Fast response, directly integrated with the Prometheus API
Simple configuration, can be set up in a few minutes
Supports multiple popular AI clients
Limitations
Requires network permissions to access the Prometheus server
Complex queries may still require manual writing of PromQL
Large - scale data queries may affect the performance of Prometheus

How to use

Install the MCP server
Install the Prometheus MCP server via npm or Docker
Configure the client
Add the MCP server configuration to your AI client
Start querying
Enter natural language query instructions in the AI chat interface

Usage examples

Basic metric query
Query the current system CPU usage
Trend analysis
Analyze the change trend of the API response time
Environment comparison
Compare the error rates of different environments

Frequently Asked Questions

What version of Node.js is required?
How to protect the security of Prometheus access?
Why do some queries return empty results?

Related resources

Prometheus official documentation
Complete documentation for the Prometheus monitoring system
GitHub repository
Project source code and issue tracking
MCP protocol documentation
Official description of the Model Context Protocol

Installation

Copy the following command to your Client for configuration
{
  "mcpServers": {
    "prometheus": {
      "command": "npx",
      "args": ["prometheus-mcp@latest", "stdio"],
      "env": {
        "PROMETHEUS_URL": "http://localhost:9090"
      }
    }
  }
}

{
  "mcpServers": {
    "prometheus": {
      "command": "npx",
      "args": ["mcp-remote", "http://localhost:3000/mcp"]
    }
  }
}

{
  "mcpServers": {
    "prometheus": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "--init",
        "--pull=always",
        "-e",
        "PROMETHEUS_URL=http://host.docker.internal:9090",
        "ghcr.io/idanfishman/prometheus-mcp",
        "stdio"
      ]
    }
  }
}
Note: Your key is sensitive information, do not share it with anyone.

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