Prometheus MCP Server
MCP serverMonitoring & opsGive your AI access to your Prometheus metrics. Once added, it can look up metrics and run PromQL queries, so you can ask questions about your systems and get answers straight from your monitoring data.
Unavailable. This server has no hosted endpoint yet, so Ahel can't serve it.
Add to setup to save this item as a reference. Ahel cannot run it, and signing in will not install it.
What your AI can do with it
- Look up metrics stored in Prometheus
- Run PromQL queries against your monitoring data
- Retrieve metric values on demand
- Answer questions about your systems based on their metrics
Getting started
- Save this item in Your setup as a reference.
- Read the source or reference documentation for its setup requirements. Saving it here does not connect it to your AI.
- Check this page for availability before trying to install it through Ahel.
From the project's README
As published by pab1it0/prometheus-mcp-server in README.md.
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
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>"
}
}
}
}
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
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>"
}
}
}
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)
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
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.
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
Signals
- GitHub stars
- 517
- Forks
- 103
- Last commit
- Oct 2026
Advanced
- Delivery
- prometheus-mcp-server MCP server → your Ahel connector (mcp.ahel.ai) → your AI.
- Item type
- mcp-server
- Key
io-github-pab1it0-prometheus-mcp-server- Source
- github.com/pab1it0/prometheus-mcp-server
github.com/pab1it0/prometheus-mcp-server
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