Which integrations are available for this server?

Provides tools for executing PromQL queries, discovering and exploring metrics, and retrieving metadata from a Prometheus server.

How do I use Prometheus MCP Server?

1. Click on "Install Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@Prometheus MCP Server what is the average CPU usage across all hosts?" That's it! The server will respond to your query, and you can continue using it as needed. Here is a step-by-step guide with screenshots.

Prometheus MCP Server

by raihan0824

Overview Schema Related Servers Score Discussions

Python

Remote

Prometheus MCP Server

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.

Quick Start

🚀 For End Users (PyPI)

# Install and run in one command
uvx --from raihan0824-prometheus-mcp-server prometheus-mcp-server

🛠️ For Developers (Local)

# Clone and install in development mode
git clone https://github.com/raihan0824/prometheus-mcp-server.git
cd prometheus-mcp-server
uv pip install -e .
prometheus-mcp-server

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.

Installation

Option 1: Install from PyPI (Recommended for Users)

# Using uvx (recommended for Claude Desktop)
uvx --from raihan0824-prometheus-mcp-server prometheus-mcp-server

# Using pip
pip install raihan0824-prometheus-mcp-server

# Using uv
uv add raihan0824-prometheus-mcp-server

Option 2: Install from Source (For Development)

# Clone the repository
git clone https://github.com/raihan0824/prometheus-mcp-server.git
cd prometheus-mcp-server

# Install with uv (development mode)
uv pip install -e .

# Or install with pip (development mode)
pip install -e .

Usage

For End Users (Using PyPI Package)

If you want to use the pre-built package from PyPI:

# Install and run in one command
uvx --from raihan0824-prometheus-mcp-server prometheus-mcp-server

# Or install permanently
pip install raihan0824-prometheus-mcp-server
prometheus-mcp-server

For Developers (Local Development)

If you want to modify the code or contribute:

# Clone and install in development mode
git clone https://github.com/raihan0824/prometheus-mcp-server.git
cd prometheus-mcp-server
uv pip install -e .

# Run the development version
prometheus-mcp-server

Ensure your Prometheus server is accessible from the environment where you'll run this MCP server.
Configure the environment variables for your Prometheus server, either through a .env file or system environment variables:

# Required: Prometheus configuration
PROMETHEUS_URL=http://your-prometheus-server:9090

# Optional: Authentication credentials (if needed)
# Choose one of the following authentication methods if required:

# For basic auth
PROMETHEUS_USERNAME=your_username
PROMETHEUS_PASSWORD=your_password

# For bearer token auth
PROMETHEUS_TOKEN=your_token

# Optional: Custom MCP configuration
PROMETHEUS_MCP_SERVER_TRANSPORT=stdio # Choose between http, stdio, sse. If undefined, stdio is set as the default transport.

# Optional: Only relevant for non-stdio transports
PROMETHEUS_MCP_BIND_HOST=localhost # if undefined, 127.0.0.1 is set by default.
PROMETHEUS_MCP_BIND_PORT=8080 # if undefined, 8080 is set by default.

# Optional: For multi-tenant setups like Cortex, Mimir or Thanos
ORG_ID=your_organization_id

Add the server configuration to your client configuration file. For example, for Claude Desktop:

Option A: Using uvx with PyPI package (Recommended for Users)

{
  "mcpServers": {
    "prometheus": {
      "command": "uvx",
      "args": [
        "--from",
        "raihan0824-prometheus-mcp-server",
        "prometheus-mcp-server"
      ],
      "env": {
        "PROMETHEUS_URL": "<your-prometheus-url>",
        "PROMETHEUS_USERNAME": "<your-username>",
        "PROMETHEUS_PASSWORD": "<your-password>"
      }
    }
  }
}

Option B: Using uvx with local repository

{
  "mcpServers": {
    "prometheus": {
      "command": "uvx",
      "args": [
        "--directory",
        "/path/to/prometheus-mcp-server",
        "run",
        "prometheus-mcp-server"
      ],
      "env": {
        "PROMETHEUS_URL": "<your-prometheus-url>",
        "PROMETHEUS_USERNAME": "<your-username>",
        "PROMETHEUS_PASSWORD": "<your-password>"
      }
    }
  }
}

Option C: Using uvx with Git repository

{
  "mcpServers": {
    "prometheus": {
      "command": "uvx",
      "args": [
        "run",
        "--from",
        "git+https://github.com/raihan0824/prometheus-mcp-server.git",
        "prometheus-mcp-server"
      ],
      "env": {
        "PROMETHEUS_URL": "<your-prometheus-url>",
        "PROMETHEUS_USERNAME": "<your-username>",
        "PROMETHEUS_PASSWORD": "<your-password>"
      }
    }
  }
}

Option D: Using Docker (Legacy)

{
  "mcpServers": {
    "prometheus": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "-e",
        "PROMETHEUS_URL",
        "ghcr.io/pab1it0/prometheus-mcp-server:latest"
      ],
      "env": {
        "PROMETHEUS_URL": "<url>",
        "PROMETHEUS_MCP_SERVER_TRANSPORT": "http",
        "PROMETHEUS_MCP_BIND_HOST": "localhost",
        "PROMETHEUS_MCP_BIND_PORT": "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 .

Project Structure

The project has been organized with a src directory structure:

prometheus-mcp-server/
├── src/
│   └── prometheus_mcp_server/
│       ├── __init__.py      # Package initialization
│       ├── server.py        # MCP server implementation
│       ├── main.py          # Main application logic
├── Dockerfile               # Docker configuration
├── docker-compose.yml       # Docker Compose configuration
├── .dockerignore            # Docker ignore file
├── pyproject.toml           # Project configuration
└── README.md                # This file

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

Tests are organized into:

Configuration validation tests
Server functionality tests
Error handling tests
Main application tests

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

This server cannot be installed

license - permissive license

quality - not tested

maintenance

How are these scores calculated?

Resources

GitHub Repository

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