PluginBench
MCP Server
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MIT

Prometheus MCP Server MCP Server

io.github.pab1it0/prometheus-mcp-server

Query Prometheus metrics and execute PromQL through AI assistants with MCP.

What is the Prometheus MCP Server MCP server?

The Prometheus MCP Server is a Model Context Protocol server that gives AI assistants like Claude and Cursor the ability to query your Prometheus metrics and execute PromQL queries. It provides standardized interfaces for metric discovery, instant/range queries, and target inspection against your Prometheus instance.

This server bridges AI assistants and Prometheus, enabling them to explore metrics, execute PromQL queries, and analyze time-series data. Use it to let Claude or Cursor investigate system metrics, troubleshoot performance issues, and answer questions about your monitoring data without leaving your IDE.

How to install Prometheus MCP Server

Copy-paste configuration for popular MCP clients.

transport: stdio
Config generated by PluginBench — verify against the source before use.
Environment / auth
  • PROMETHEUS_URL
    required

    Prometheus server URL (e.g., http://localhost:9090)

  • PROMETHEUS_URL_SSL_VERIFY

    Set to False to disable SSL verification

  • PROMETHEUS_DISABLE_LINKS

    Set to True to disable Prometheus UI links in query results (saves context tokens in MCP clients)

  • PROMETHEUS_USERNAME

    Username for Prometheus basic authentication

  • PROMETHEUS_PASSWORD
    secret

    Password for Prometheus basic authentication

  • PROMETHEUS_TOKEN
    secret

    Bearer token for Prometheus authentication

  • ORG_ID

    Organization ID for multi-tenant Prometheus setups

  • PROMETHEUS_CLIENT_CERT

    Path to client certificate file for mutual TLS authentication

  • PROMETHEUS_CLIENT_KEY

    Path to client private key file for mutual TLS authentication

  • PROMETHEUS_MCP_SERVER_TRANSPORT

    MCP server transport type (stdio, http, or sse)

  • PROMETHEUS_MCP_BIND_HOST

    Host address for HTTP/SSE transport (default: 127.0.0.1)

  • PROMETHEUS_MCP_BIND_PORT

    Port number for HTTP/SSE transport (default: 8080)

  • PROMETHEUS_MCP_STATELESS_HTTP

    Enable stateless HTTP mode for multi-replica support (default: false)

  • PROMETHEUS_CUSTOM_HEADERS

    Custom headers as JSON string to include in Prometheus requests

~/Library/Application Support/Claude/claude_desktop_config.json
{
  "mcpServers": {
    "prometheus-mcp-server": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "ghcr.io/pab1it0/prometheus-mcp-server:1.6.2"
      ],
      "env": {
        "PROMETHEUS_URL": "<YOUR_PROMETHEUS_URL>",
        "PROMETHEUS_URL_SSL_VERIFY": "<YOUR_PROMETHEUS_URL_SSL_VERIFY>",
        "PROMETHEUS_DISABLE_LINKS": "<YOUR_PROMETHEUS_DISABLE_LINKS>",
        "PROMETHEUS_USERNAME": "<YOUR_PROMETHEUS_USERNAME>",
        "PROMETHEUS_PASSWORD": "<YOUR_PROMETHEUS_PASSWORD>",
        "PROMETHEUS_TOKEN": "<YOUR_PROMETHEUS_TOKEN>",
        "ORG_ID": "<YOUR_ORG_ID>",
        "PROMETHEUS_CLIENT_CERT": "<YOUR_PROMETHEUS_CLIENT_CERT>",
        "PROMETHEUS_CLIENT_KEY": "<YOUR_PROMETHEUS_CLIENT_KEY>",
        "PROMETHEUS_MCP_SERVER_TRANSPORT": "<YOUR_PROMETHEUS_MCP_SERVER_TRANSPORT>",
        "PROMETHEUS_MCP_BIND_HOST": "<YOUR_PROMETHEUS_MCP_BIND_HOST>",
        "PROMETHEUS_MCP_BIND_PORT": "<YOUR_PROMETHEUS_MCP_BIND_PORT>",
        "PROMETHEUS_MCP_STATELESS_HTTP": "<YOUR_PROMETHEUS_MCP_STATELESS_HTTP>",
        "PROMETHEUS_CUSTOM_HEADERS": "<YOUR_PROMETHEUS_CUSTOM_HEADERS>"
      }
    }
  }
}

Tools & capabilities

Tools this server exposes to the agent.

  • health_check — Health check endpoint for container monitoring and status verification
  • execute_query — Execute a PromQL instant query against Prometheus
  • execute_range_query — Execute a PromQL range query with start time, end time, and step interval
  • list_metrics — List all available metrics in Prometheus with pagination and filtering support
  • get_metric_metadata — Get metadata for one metric or bulk metadata with optional filtering
  • get_targets — Get scrape targets, with server-side state/scrape_pool filtering and optional pagination

Use cases

  • Execute PromQL queries to investigate system performance metrics and anomalies
  • Discover available metrics and explore their metadata to understand your monitoring setup
  • Retrieve scrape target status to verify which endpoints are being monitored
  • Analyze time-series data with range queries across custom time windows and step intervals
  • Troubleshoot infrastructure issues by querying metrics directly from your IDE

Prometheus MCP Server MCP server FAQ

What is the Prometheus MCP Server?

It's an MCP server that connects AI assistants to your Prometheus instance, allowing them to execute PromQL queries, list metrics, and explore monitoring data.

Is it free?

Yes, the Prometheus MCP Server is open-source under the MIT license.

How do I install it in Cursor or Claude?

Add the server to your MCP configuration with the Docker image `ghcr.io/pab1it0/prometheus-mcp-server:latest` and set the `PROMETHEUS_URL` environment variable to your Prometheus server URL.

What authentication methods are supported?

Basic authentication (username/password), bearer token authentication, mutual TLS (client certificate/key), and custom headers.

Do I need Docker to run this?

Docker is the recommended method, but you can also deploy it to Kubernetes using the provided Helm chart or run it directly if you have Python 3.10+.

Can I run multiple instances targeting different Prometheus servers?

Yes, use the `TOOL_PREFIX` environment variable to prefix tool names, allowing you to run multiple instances in the same client targeting different environments.

README (reference)

Source of truth, from the repository.

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

<details> <summary><b>Claude Desktop</b></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><b>Claude Code</b></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><b>VS Code / Cursor / Windsurf</b></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><b>Docker Desktop</b></summary>

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

<a href="https://hub.docker.com/open-desktop?url=https://open.docker.com/dashboard/mcp/servers/id/prometheus/config?enable=true"> <img src="https://img.shields.io/badge/+%20Add%20to-Docker%20Desktop-2496ED?style=for-the-badge&logo=docker&logoColor=white" alt="Add to Docker Desktop" /> </a>
  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)

</details> <details> <summary><b>Manual Docker Setup</b></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><b>Helm Chart (Kubernetes)</b></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 1.1.1 \
  --set prometheus.url="http://prometheus:9090"

With authentication:

helm install prometheus-mcp-server \
  oci://ghcr.io/pab1it0/charts/prometheus-mcp-server \
  --version 1.1.1 \
  --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 1.1.1 \
  -f values.yaml

See the chart values for all available configuration options.

</details>

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_MCP_STATELESS_HTTPEnable stateless HTTP mode for multi-replica supportNo (default: False)
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 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


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