Prometheus MCP

by etruong42

Not rated
GitHub

About

Expose Prometheus monitoring tools to an LLM for querying and analysis.

Details

Author
etruong42
Categories
Developer Tools, Infrastructure, Other

Setup

Install Prometheus MCP in your MCP client (Claude Desktop, Cursor, Windsurf, and others).

Repository: https://github.com/etruong42/prometheus-mcp

Follow the installation instructions in the repository README, then restart your MCP client.

Installuv:https://docs.astral.sh/uv/getting-started/installation/

uv add "mcp[cli]" pillow google-auth matplotlib requests python-dotenv
uv --directory "/directory/to/prometheus-mcp" run server.py

So you may add this MCP server to your Claude MCP server configuration

{ "mcpServers": { "Prometheus MCP": { "command": "/path/to/uv", "args": [ "--directory", "/directory/to/prometheus-mcp", "run", "server.py" ] } } }

SeeMCP Quickstartfor more details for Claude specific instructions.

This is a web browser that enables your coding agent, such as Claude Code, to visit websites on your behalf and assist you in identifying bugs or creating UI test cases.

Access Prometheus metrics and queries through standardized MCP interfaces.

Interact with your Prometheus monitoring infrastructure using natural language.

An MCP server for integrating with Prometheus to query metrics.

Access and manage Grafana resources, including dashboards, datasources, Prometheus, Loki, and alerting.

Access Grafana resources like dashboards, datasources, Prometheus, Loki, and alerts.

MCP server for Grafana — manage dashboards, datasources, alerts, folders, and annotations over stdio

Interact with Honeycomb observability data using the Model Context Protocol.

Retrieve and analyze time-series data from Prometheus databases using PromQL queries.

A Prometheus MCP server with full API support for comprehensive management and deep interaction with Prometheus beyond basic query support. Written in go, it is a single binary install that is capable of STDIO, SSE, and HTTP transports for complex deployments.

Seamlessly bring real-time production context—logs, metrics, and traces—into your local environment to auto-fix code faster.

No reviews yet — be the first

Sign in to leave a review

Use Google, GitHub, or an email account so ratings stay tied to real people.

Email sign in

No reviews posted yet.