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loglmhq_mcp-server-prometheus
Mirror ofhttps://github.com/loglmhq/mcp-server-prometheus
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mcp-server-prometheus
MCP server for interacting with Prometheus metrics and data.
This is a TypeScript-based MCP server that implements a Prometheus API interface. It provides a bridge between Claude and your Prometheus server through the Model Context Protocol (MCP).
Demo
Features
Resources
- List and access Prometheus metric schema
- Each metric resource provides:
- Metric name and description
- Detailed metadata from Prometheus
- Statistical information (count, min, max)
- JSON mime type for structured data access
Current Capabilities
- List all available Prometheus metrics with descriptions
- Read detailed metric information including:
- Metadata and help text
- Current statistical data (count, min, max values)
- Basic authentication support for secured Prometheus instances
Configuration
The server requires the following environment variable:
-
PROMETHEUS_URL
: The base URL of your Prometheus instance
Optional authentication configuration:
-
PROMETHEUS_USERNAME
: Username for basic auth (if required) -
PROMETHEUS_PASSWORD
: Password for basic auth (if required)
Development
Install dependencies:
npm install
Build the server:
npm run build
For development with auto-rebuild:
npm run watch
Installation
To use with Claude Desktop, add the server config:
On MacOS: ~/Library/Application Support/Claude/claude_desktop_config.json
On Windows: %APPDATA%/Claude/claude_desktop_config.json
{
"mcpServers": {
"mcp-server-prometheus": {
"command": "/path/to/mcp-server-prometheus/build/index.js",
"env": {
"PROMETHEUS_URL": "http://your-prometheus-instance:9090"
}
}
}
}
Debugging
Since MCP servers communicate over stdio, debugging can be challenging. We recommend using the MCP Inspector:
npm run inspector
The Inspector will provide a URL to access debugging tools in your browser.
API Structure
The server exposes Prometheus metrics through the following URI structure:
- Base URI:
http://your-prometheus-instance:9090
- Metric URIs:
http://your-prometheus-instance:9090/metrics/{metric_name}
Each metric resource returns JSON data containing:
- Metric name
- Metadata (help text, type)
- Current statistics (count, min, max)
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Reviews

user_tEMhrcWf
As an avid user of the MCP platform, I found the Kaggle-MCP: Kaggle API Integration for Claude AI to be extremely useful. The seamless integration with Kaggle API has significantly enhanced my data science and machine learning projects. Kudos to the author 54yyyu for creating such a valuable tool! Highly recommend it to anyone looking to leverage Kaggle datasets more efficiently.