pab1it0/prometheus-mcp-server

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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.

概览

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. - Prometheus server accessible from your environment - MCP-compatible client (Claude Desktop, VS Code, Cursor, Windsurf, etc.) Add to your Claude Desktop configuration: Add to your MCP settings in the respective IDE: The easiest way to run the Prometheus MCP server is through Docker Desktop: 1. : Visit the Prometheus MCP Server on Docker Hub and click the button above 2. : Use Docker Desktop's MCP Toolkit extension to discover and install the server

README

Prometheus MCP Server

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

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 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

View this README on GitHub

安装

docker run -i --rm -e PROMETHEUS_URL ghcr.io/pab1it0/prometheus-mcp-server:latest

配置

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