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MCP server for Prometheus integration

Project description

Prometheus MCP Server

GitHub Container Registry GitHub Release Codecov Python License

Give AI assistants the power to query your Prometheus metrics.

A Model Context Protocol (MCP) server that provides access to your Prometheus metrics and queries through standardized MCP interfaces, allowing AI assistants to execute PromQL queries and analyze your metrics data.

Getting Started

Prerequisites

  • Prometheus server accessible from your environment
  • MCP-compatible client (Claude Desktop, VS Code, Cursor, Windsurf, etc.)

Installation Methods

Claude Desktop

Add to your Claude Desktop configuration:

{
  "mcpServers": {
    "prometheus": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "-e",
        "PROMETHEUS_URL",
        "ghcr.io/pab1it0/prometheus-mcp-server:latest"
      ],
      "env": {
        "PROMETHEUS_URL": "<your-prometheus-url>"
      }
    }
  }
}
Claude Code

Install via the Claude Code CLI:

claude mcp add prometheus --env PROMETHEUS_URL=http://your-prometheus:9090 -- docker run -i --rm -e PROMETHEUS_URL ghcr.io/pab1it0/prometheus-mcp-server:latest
VS Code / Cursor / Windsurf

Add to your MCP settings in the respective IDE:

{
  "prometheus": {
    "command": "docker",
    "args": [
      "run",
      "-i",
      "--rm",
      "-e",
      "PROMETHEUS_URL",
      "ghcr.io/pab1it0/prometheus-mcp-server:latest"
    ],
    "env": {
      "PROMETHEUS_URL": "<your-prometheus-url>"
    }
  }
}
Docker Desktop

The easiest way to run the Prometheus MCP server is through Docker Desktop:

Add to Docker Desktop
  1. Via MCP Catalog: Visit the Prometheus MCP Server on Docker Hub and click the button above

  2. Via MCP Toolkit: Use Docker Desktop's MCP Toolkit extension to discover and install the server

  3. Configure your connection using environment variables (see Configuration Options below)

Manual Docker Setup

Run directly with Docker:

# With environment variables
docker run -i --rm \
  -e PROMETHEUS_URL="http://your-prometheus:9090" \
  ghcr.io/pab1it0/prometheus-mcp-server:latest

# With authentication
docker run -i --rm \
  -e PROMETHEUS_URL="http://your-prometheus:9090" \
  -e PROMETHEUS_USERNAME="admin" \
  -e PROMETHEUS_PASSWORD="password" \
  ghcr.io/pab1it0/prometheus-mcp-server:latest

Configuration Options

Variable Description Required
PROMETHEUS_URL URL of your Prometheus server Yes
PROMETHEUS_URL_SSL_VERIFY Set to False to disable SSL verification No
PROMETHEUS_DISABLE_LINKS Set to True to disable Prometheus UI links in query results (saves context tokens) No
PROMETHEUS_REQUEST_TIMEOUT Request timeout in seconds to prevent hanging requests (DDoS protection) No (default: 30)
PROMETHEUS_USERNAME Username for basic authentication No
PROMETHEUS_PASSWORD Password for basic authentication No
PROMETHEUS_TOKEN Bearer token for authentication No
PROMETHEUS_CLIENT_CERT Path to client certificate file for mutual TLS authentication No
PROMETHEUS_CLIENT_KEY Path to client private key file for mutual TLS authentication No
REQUESTS_CA_BUNDLE Path to CA bundle file for verifying the server's TLS certificate (standard requests library env var) No
ORG_ID Organization ID for multi-tenant setups No
PROMETHEUS_MCP_SERVER_TRANSPORT Transport mode (stdio, http, sse) No (default: stdio)
PROMETHEUS_MCP_BIND_HOST Host for HTTP transport No (default: 127.0.0.1)
PROMETHEUS_MCP_BIND_PORT Port for HTTP transport No (default: 8080)
PROMETHEUS_CUSTOM_HEADERS Custom headers as JSON string No
TOOL_PREFIX Prefix for all tool names (e.g., staging results in staging_execute_query). Useful for running multiple instances targeting different environments in Cursor No

Available Tools

Tool Category Description
health_check System Health check endpoint for container monitoring and status verification
execute_query Query Execute a PromQL instant query against Prometheus
execute_range_query Query Execute a PromQL range query with start time, end time, and step interval
list_metrics Discovery List all available metrics in Prometheus with pagination and filtering support
get_metric_metadata Discovery Get metadata for one metric or bulk metadata with optional filtering
get_targets Discovery Get information about all scrape targets

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.

Features

  • Execute PromQL queries against Prometheus
  • Discover and explore metrics
    • List available metrics
    • Get metadata for specific metrics
    • Search metric metadata by name or description in a single call
    • View instant query results
    • View range query results with different step intervals
  • Authentication support
    • Basic auth from environment variables
    • Bearer token auth from environment variables
  • Docker containerization support
  • Provide interactive tools for AI assistants

Development

Contributions are welcome! Please see our Contributing Guide for detailed information on how to get started, coding standards, and the pull request process.

This project uses uv to manage dependencies. Install uv following the instructions for your platform:

curl -LsSf https://astral.sh/uv/install.sh | sh

You can then create a virtual environment and install the dependencies with:

uv venv
source .venv/bin/activate  # On Unix/macOS
.venv\Scripts\activate     # On Windows
uv pip install -e .

Testing

The project includes a comprehensive test suite that ensures functionality and helps prevent regressions.

Run the tests with pytest:

# Install development dependencies
uv pip install -e ".[dev]"

# Run the tests
pytest

# Run with coverage report
pytest --cov=src --cov-report=term-missing

When adding new features, please also add corresponding tests.

License

MIT


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