Mcp Monitoring
@reemshai10
About Mcp Monitoring
A sophisticated Model Context Protocol (MCP) server that provides intelligent monitoring and observability integration. This server enables natural language interactions with Prometheus, AlertManager, and Grafana through chat-style commands, advanced query processing, and compreh
Config
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"monitoring-mcp": {
"command": "node",
"args": [
"/Users/MCP/mcp-monitoring/dist/index.js"
],
"env": {
"PROMETHEUS_URL": "${input:prometheus_base_url}",
"ALERTMANAGER_URL": "${input:alertmanager_base_url}",
"GRAFANA_URL": "${input:grafana_base_url}",
"GRAFANA_API_KEY": "${input:grafana_api_key}"
}
}
}
}Tools
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Overview
What is Mcp Monitoring?
Mcp Monitoring is an MCP server that lets DevOps, SRE, and development teams query monitoring systems (Prometheus, AlertManager, Grafana) using natural language. It parses questions about service failures, availability, alerts, and metrics, then generates optimized PromQL queries and returns human-readable answers.
How to use Mcp Monitoring?
Configure the server in your MCP client (e.g., VS Code) by setting the command to node with the path to dist/index.js. Set environment variables: PROMETHEUS_URL, ALERTMANAGER_URL, GRAFANA_URL, and GRAFANA_API_KEY. Then ask natural-language questions like "How many times did [service] fail in the last [time period]?" or "Show me jenkins outages yesterday".
Key features of Mcp Monitoring
- Natural language query processing for monitoring data
- Intelligent PromQL generation based on intent
- Result caching and automatic time-range step sizing
- Supports current alerts, historical incidents, availability analysis
- Read-only operations with secure API token storage
Use cases of Mcp Monitoring
- Incident response: quickly assess service health and failure patterns
- Postmortem analysis: historical incident data for root cause analysis
- SLI/SLO monitoring: service availability and performance tracking
- Deployment monitoring: track deployment success/failure rates
- Alert fatigue management: identify noisy alerts and optimization opportunities
FAQ from Mcp Monitoring
What monitoring services does it support?
Prometheus, AlertManager, and Grafana. It automatically recognizes services like cleanup-zuultmp, opengrok, jenkins, grafana, prometheus, alertmanager, gerrit, nginx, mysql, redis, elasticsearch.
How are credentials handled?
Secure API tokens for Grafana are stored via environment variables (GRAFANA_API_KEY, PROMETHEUS_URL, etc.), with support for basic auth. All data access is read-only.
What happens if there’s a connection error or timeout?
Common errors include ECONNREFUSED (check network connectivity), 401 Unauthorized (verify tokens), and timeout of 30000ms exceeded (reduce query complexity or time range). Enable debug mode with DEBUG=monitoring-mcp.
Can I ask about any time range?
Yes, the server parses temporal expressions like "last 2 weeks", "yesterday", "this month" into date ranges and automatically adjusts query step sizes.
Does it modify monitoring data?
No. All operations are read-only by design, with no data modification capabilities.
Frequently asked questions
What monitoring services does it support?
Prometheus, AlertManager, and Grafana. It automatically recognizes services like cleanup-zuultmp, opengrok, jenkins, grafana, prometheus, alertmanager, gerrit, nginx, mysql, redis, elasticsearch.
How are credentials handled?
Secure API tokens for Grafana are stored via environment variables (`GRAFANA_API_KEY`, `PROMETHEUS_URL`, etc.), with support for basic auth. All data access is read-only.
What happens if there’s a connection error or timeout?
Common errors include `ECONNREFUSED` (check network connectivity), `401 Unauthorized` (verify tokens), and timeout of 30000ms exceeded (reduce query complexity or time range). Enable debug mode with `DEBUG=monitoring-mcp`.
Can I ask about any time range?
Yes, the server parses temporal expressions like "last 2 weeks", "yesterday", "this month" into date ranges and automatically adjusts query step sizes.
Does it modify monitoring data?
No. All operations are read-only by design, with no data modification capabilities.
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