Prometheus MCP Server

![GitHub Container Registry](https://github.com/users/pab1it0/packages/container/package/prometheus-mcp-server) ![Helm Chart](https://github.com/pab1it0/prometheus-mcp-server/pkgs/container/charts%2Fprometheus-mcp-server) ![GitHub Release](https://github.com/pab1it0/prometheus-mcp-server/releases) ![Codecov](https://codecov.io/gh/pab1it0/prometheus-mcp-server) !Python ![License](https://github.com/pab1it0/prometheus-mcp-server/blob/main/LICENSE)

Give AI assistants the power to query your Prometheus metrics.

A [Model Context Protocol][mcp] (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.

[mcp]: https://modelcontextprotocol.io

Getting Started

Prerequisites

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

Installation Methods

<details> <summary>Claude Desktop</summary>

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>"
      }
    }
  }
}

</details>

<details> <summary>Claude Code</summary>

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

</details>

<details> <summary>VS Code / Cursor / Windsurf</summary>

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>"
    }
  }
}

</details>

<details> <summary>Docker Desktop</summary>

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

Via MCP Catalog: Visit the Prometheus MCP Server on Docker Hub and click the button above

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

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

</details>

<details> <summary>Manual Docker Setup</summary>

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

</details>

<details> <summary>Helm Chart (Kubernetes)</summary>

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. </details>

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_MCP_STATELESS_HTTP | Enable stateless HTTP mode for multi-replica support | No (default: False) | | 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 scrape targets, with server-side state/scrape_pool filtering and optional pagination |

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

---

prometheus-mcp-server