Prometheus▌
by idanfishman
Integrate with Prometheus for real-time performance analysis, process monitoring, and advanced Prometheus 2.0 metric dis
Integrates with Prometheus monitoring systems to provide direct access to time-series metrics through specialized tools for discovering available metrics and labels, retrieving metadata and target information, and executing PromQL queries for real-time performance analysis and operational intelligence.
best for
- / DevOps engineers monitoring system performance
- / SREs analyzing operational metrics
- / Developers debugging application performance
- / Teams wanting natural language access to metrics
capabilities
- / Execute PromQL queries against Prometheus
- / Discover available metrics and labels
- / Retrieve target and metadata information
- / Analyze time-series performance data
- / Browse monitoring infrastructure through natural language
what it does
Connects AI assistants to Prometheus monitoring systems for querying time-series metrics and analyzing performance data through natural language. Execute PromQL queries and retrieve operational metrics directly in your AI chat.
about
Prometheus is a community-built MCP server published by idanfishman that provides AI assistants with tools and capabilities via the Model Context Protocol. Integrate with Prometheus for real-time performance analysis, process monitoring, and advanced Prometheus 2.0 metric dis It is categorized under developer tools, analytics data.
how to install
You can install Prometheus in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.
license
MIT
Prometheus is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.
readme
Integrate with Prometheus for real-time performance analysis, process monitoring, and advanced Prometheus 2.0 metric dis
TL;DR: Connects AI assistants to Prometheus monitoring systems for querying time-series metrics and analyzing performance data through natural language. Execute PromQL queries and retrieve operational metrics directly in your AI chat.
What it does
- Execute PromQL queries against Prometheus
- Discover available metrics and labels
- Retrieve target and metadata information
- Analyze time-series performance data
- Browse monitoring infrastructure through natural language
Best for
- DevOps engineers monitoring system performance
- SREs analyzing operational metrics
- Developers debugging application performance
- Teams wanting natural language access to metrics
Highlights
- Works with existing Prometheus servers
- LLM-optimized JSON responses
- Configurable tool permissions
FAQ
- What is the Prometheus MCP server?
- Prometheus is a Model Context Protocol (MCP) server profile on explainx.ai. MCP lets AI hosts (e.g. Claude Desktop, Cursor) call tools and resources through a standard interface; this page summarizes categories, install hints, and community ratings.
- How do MCP servers relate to agent skills?
- Skills are reusable instruction packages (often SKILL.md); MCP servers expose live capabilities. Teams frequently combine both—skills for workflows, MCP for APIs and data. See explainx.ai/skills and explainx.ai/mcp-servers for parallel directories.
- How are reviews shown for Prometheus?
- This profile displays 10 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.5 out of 5—verify behavior in your own environment before production use.
Ratings
4.5★★★★★10 reviews- ★★★★★Shikha Mishra· Oct 10, 2024
Prometheus is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
- ★★★★★Piyush G· Sep 9, 2024
We evaluated Prometheus against two servers with overlapping tools; this profile had the clearer scope statement.
- ★★★★★Chaitanya Patil· Aug 8, 2024
Useful MCP listing: Prometheus is the kind of server we cite when onboarding engineers to host + tool permissions.
- ★★★★★Sakshi Patil· Jul 7, 2024
Prometheus reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
- ★★★★★Ganesh Mohane· Jun 6, 2024
I recommend Prometheus for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
- ★★★★★Oshnikdeep· May 5, 2024
Strong directory entry: Prometheus surfaces stars and publisher context so we could sanity-check maintenance before adopting.
- ★★★★★Dhruvi Jain· Apr 4, 2024
Prometheus has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
- ★★★★★Rahul Santra· Mar 3, 2024
According to our notes, Prometheus benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
- ★★★★★Pratham Ware· Feb 2, 2024
We wired Prometheus into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
- ★★★★★Yash Thakker· Jan 1, 2024
Prometheus is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.