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A Model Context Protocol (MCP) server that enables AI agents and LLMs to query and analyze Prometheus metrics through standardized interfaces.

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Prometheus MCP Server

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A Model Context Protocol (MCP) server for Prometheus.

This provides access to your Prometheus metrics and queries through standardized MCP interfaces, allowing AI assistants to execute PromQL queries and analyze your metrics data.

Features

  • Execute PromQL queries against Prometheus

  • Discover and explore metrics

    • List available metrics
    • Get metadata for specific metrics
    • 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

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.

Getting Started

Prerequisites

  • Prometheus server accessible from your environment
  • Docker Desktop (recommended) or Docker CLI
  • 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_USERNAME Username for basic authentication No
PROMETHEUS_PASSWORD Password for basic authentication No
PROMETHEUS_TOKEN Bearer token for authentication 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)

Development

Contributions are welcome! Please open an issue or submit a pull request if you have any suggestions or improvements.

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.

Tools

Tool Category Description
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
get_metric_metadata Discovery Get metadata for a specific metric
get_targets Discovery Get information about all scrape targets

License

MIT


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