Provides tools for querying real-time and historical metrics data, discovering available metrics, retrieving metric metadata, and monitoring scrape targets from Prometheus monitoring systems.
Prometheus MCP Server
A Model Context Protocol (MCP) server that provides seamless integration with Prometheus, enabling AI assistants to query metrics, discover available data, and analyze system performance through natural language interactions.
Features
Real-time Metrics Access - Query current and historical metrics data
Metrics Discovery - Find available metrics and monitoring targets
Multiple Auth Methods - Basic auth, bearer tokens, and TLS support
Type-safe - Full TypeScript implementation
MCP Configuration
Using npx (Recommended)
Add to your MCP client settings:
Using global installation
First install the package globally:
Then configure your MCP client:
Environment Variables
Available Tools
Tool | Description | Use Case |
| Execute PromQL instant query | Get current metric values, alerts status |
| Execute PromQL range query | Analyze trends, create graphs, historical data |
| Discover available metrics | Explore what metrics are available in your system |
| Get metric metadata | Understand metric types, descriptions, and units |
| Get scrape targets info | Monitor scraping health and service discovery |
Example Usage
Ask your AI assistant natural language questions:
"What's the current CPU usage across all servers?"
"Show me HTTP request rates for the last 6 hours"
"Which services have the highest memory consumption?"
"Are there any failing health checks?"
"What metrics are available for monitoring my database?"
Development
Connection Methods
1. No Authentication
2. Basic Authentication
3. Bearer Token
Additional Options
For self-signed certificates or development:
License
MIT
remote-capable server
The server can be hosted and run remotely because it primarily relies on remote services or has no dependency on the local environment.
A Model Context Protocol server that enables AI assistants to query Prometheus metrics, discover available data, and analyze system performance through natural language interactions.
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