MCP Prometheus Server

Created By

drewstreiba year ago

A sophisticated MCP server for Prometheus queries demonstrating advanced Haskell practices

Overview

what is MCP Prometheus Server?

MCP Prometheus Server is a sophisticated server implementation for the Model Context Protocol (MCP) that allows access to Prometheus metrics and queries, showcasing advanced Haskell practices.

how to use MCP Prometheus Server?

To use the MCP Prometheus Server, you can either clone the repository and use the pre-built binary, build from source, or run it using Docker. Configuration is required for integration with Claude Desktop.

key features of MCP Prometheus Server?

🚀 Claude Desktop Integration - Seamless support for MCP protocol.
📊 Complete Prometheus API - Query, discover, and explore metrics.
🔍 5 Powerful Tools - Instant queries, metric discovery, and more.
🛡️ Production Ready - Comprehensive error handling and logging.
🧵 Thread Safe - Strict evaluation prevents lazy I/O hangs.
🔧 Haskell Best Practices - Proper exception handling and robust operation.

use cases of MCP Prometheus Server?

Integrating Prometheus metrics into applications.
Monitoring system performance through Prometheus queries.
Developing Haskell applications with robust error handling and logging.

FAQ from MCP Prometheus Server?

Can I run MCP Prometheus Server in Docker?

Yes! You can run it using Docker for development purposes.

What are the prerequisites for building from source?

You need GHC 9.12+ and Cabal 3.0+.

How do I configure the server for Claude Desktop?

You need to add the server command to your Claude Desktop configuration file.

Project Info

Created At

a year ago

Updated At

a year ago

Author Name

drewstreib

Star

Language

Haskell

License

BSD-3-Clause license

Recommend Servers

View All

Concordance

@matharrismma

Language models generate; Concordance verifies. The verify tool checks a claim deterministically (no model in the loop) and returns HOLDS / BROKEN / INCOMPLETE with the worked reasoning and a sealed receipt (content_hash + cite_url) that re-fetches byte-identical or not at all. Also: ranked search over an ~11k-record library, seal_fetch to re-verify any receipt, redact to strip PII before text travels, and a sealed connection graph. Runs sovereign/offline too (stdlib-first Python). A public false-positive benchmark covers every domain: the engine has never sealed a falsehood. 38 tools live; remote endpoint at https://narrowhighway.com/mcp.

10 days ago