Prometheus MCP Server

An MCP server for integrating with Prometheus to query metrics.

GitHub

Prometheus MCP Server

GitHub Container Registry Helm Chart 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
Helm Chart (Kubernetes)

Deploy to Kubernetes using the Helm chart from the OCI registry:

helm install prometheus-mcp-server \
  oci://ghcr.io/pab1it0/charts/prometheus-mcp-server \
  --version 1.0.0 \
  --set prometheus.url="http://prometheus:9090"

With authentication:

helm install prometheus-mcp-server \
  oci://ghcr.io/pab1it0/charts/prometheus-mcp-server \
  --version 1.0.0 \
  --set prometheus.url="http://prometheus:9090" \
  --set auth.username="admin" \
  --set auth.password="secret"

With a custom values file:

helm install prometheus-mcp-server \
  oci://ghcr.io/pab1it0/charts/prometheus-mcp-server \
  --version 1.0.0 \
  -f values.yaml

See the chart values for all available configuration options.

Configuration Options

VariableDescriptionRequired
PROMETHEUS_URLURL of your Prometheus serverYes
PROMETHEUS_URL_SSL_VERIFYSet to False to disable SSL verificationNo
PROMETHEUS_DISABLE_LINKSSet to True to disable Prometheus UI links in query results (saves context tokens)No
PROMETHEUS_REQUEST_TIMEOUTRequest timeout in seconds to prevent hanging requests (DDoS protection)No (default: 30)
PROMETHEUS_USERNAMEUsername for basic authenticationNo
PROMETHEUS_PASSWORDPassword for basic authenticationNo
PROMETHEUS_TOKENBearer token for authenticationNo
PROMETHEUS_CLIENT_CERTPath to client certificate file for mutual TLS authenticationNo
PROMETHEUS_CLIENT_KEYPath to client private key file for mutual TLS authenticationNo
REQUESTS_CA_BUNDLEPath to CA bundle file for verifying the server's TLS certificate (standard requests library env var)No
ORG_IDOrganization ID for multi-tenant setupsNo
PROMETHEUS_MCP_SERVER_TRANSPORTTransport mode (stdio, http, sse)No (default: stdio)
PROMETHEUS_MCP_BIND_HOSTHost for HTTP transportNo (default: 127.0.0.1)
PROMETHEUS_MCP_BIND_PORTPort for HTTP transportNo (default: 8080)
PROMETHEUS_CUSTOM_HEADERSCustom headers as JSON stringNo
TOOL_PREFIXPrefix for all tool names (e.g., staging results in staging_execute_query). Useful for running multiple instances targeting different environments in CursorNo

Available Tools

ToolCategoryDescription
health_checkSystemHealth check endpoint for container monitoring and status verification
execute_queryQueryExecute a PromQL instant query against Prometheus
execute_range_queryQueryExecute a PromQL range query with start time, end time, and step interval
list_metricsDiscoveryList all available metrics in Prometheus with pagination and filtering support
get_metric_metadataDiscoveryGet metadata for one metric or bulk metadata with optional filtering
get_targetsDiscoveryGet 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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