Mcp Monitoring
About
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
Details
- Author
- reemshai10
- Downloads
- 324
- Categories
- Developer Tools
Jump to
- 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
Setting up with Highlight
This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:
- Download and install Highlight from highlightai.com/download
- Navigate to the plugins tab and select "Add Custom Plugin"
-
Configure the plugin with the settings below
Plugin Name
Mcp MonitoringCommand (node, npx, python, etc.)Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.
- Enable "Start Automatically" if you want the plugin to start when Highlight launches
From the repository
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".
Claude Desktop / Cursor
Paste into your MCP client config file to install this server.
{
"mcpServers": {
"mcp monitoring": {
"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}"
}
}
}
}
}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}"
}
}
}💬 Natural Language Examples
Service Failure Analysis
Q: "How many times did prevent-opengrok automation fail in the last 2 weeks?"
A: 46 failures over 2 days and 3 hours total downtime
Q: "Show me jenkins outages yesterday"
A: Detailed breakdown of jenkins service interruptions
Q: "Count critical alerts for grafana service this month"
A: Historical analysis with incident timeline
Service Availability Queries
Q: "How many times was prometheus down last week?"
A: Service downtime incidents with duration analysis
Q: "Show cleanup-zuultmp disk usage alerts"
A: Disk space warnings and critical alerts breakdown
Q: "What automation failures happened in the past 7 days?"
A: Comprehensive automation failure report
🔧 Integration Examples
VS Code MCP Configuration
{
"servers": {
"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}"
}
}
}
}
}
🎯 Use Cases
DevOps Teams
- Incident Response: Quickly assess service health and failure patterns - Postmortem Analysis: Historical incident data for root cause analysis - Capacity Planning: Trend analysis and resource utilization monitoring - Alert Fatigue Management: Identify noisy alerts and optimization opportunitiesSRE Teams
- SLI/SLO Monitoring: Service availability and performance tracking - Error Budget Analysis: Calculate error rates and availability metrics - Automated Reporting: Generate incident reports and availability summaries - Proactive Monitoring: Identify patterns before they become critical issuesDevelopment Teams
- Deployment Monitoring: Track deployment success/failure rates - Performance Regression Detection: Compare metrics across releases - Integration Testing: Monitor test environment stability - Feature Flag Impact: Assess performance impact of feature rollouts🧩 Architecture
Smart Query Processing Pipeline
1. Intent Recognition: Parse natural language to understand query type 2. Service Detection: Identify target services and components 3. Time Range Extraction: Parse temporal expressions into date ranges 4. PromQL Generation: Create optimized queries based on intent 5. Data Analysis: Process results and calculate meaningful metrics 6. Response Formatting: Present data in human-readable formatSupported Query Types
-current_alerts: Active/firing alerts right now
- historical_alerts: Past incidents and failure counts
- service_availability: Uptime/downtime analysis
- dashboard_discovery: Find relevant monitoring dashboards
- metrics: General metric queries and analysis
📈 Performance Features
- Intelligent Query Optimization: Automatic step sizing for different time ranges
- Result Caching: Avoid redundant API calls for recent queries
- Timeout Handling: Graceful handling of slow monitoring APIs
- Batch Processing: Efficient handling of multi-service queries
- Memory Management: Optimized for long-running server deployment
🔒 Security & Best Practices
Authentication
- Secure API token storage for Grafana integration - Support for basic auth with Prometheus/AlertManager - Environment variable configuration for sensitive dataNetwork Security
- HTTPS-only connections to monitoring services - Configurable timeout and retry policies - Certificate validation for secure connectionsAccess Control
- Read-only operations by design - No data modification capabilities - Audit logging for all monitoring queries🐛 Troubleshooting
Common Issues
# Connection errors
Error: connect ECONNREFUSED
Solution: Check PROMETHEUS_URL and network connectivity
Authentication failures
Error: 401 Unauthorized
Solution: Verify API tokens and authentication credentials
Query timeouts
Error: timeout of 30000ms exceeded
Solution: Reduce query complexity or time range
No data returned
Warning: No matching metrics found
Solution: Check service names and time range validity
Debug Mode
# Enable verbose logging
DEBUG=monitoring-mcp node dist/index.js
Check configuration
node -e "console.log(process.env.PROMETHEUS_URL)"
🚀 Advanced Usage
Custom Service Detection
The server automatically recognizes these services: -cleanup-zuultmp, opengrok, jenkins
- grafana, prometheus, alertmanager
- gerrit, nginx, mysql, redis, elasticsearch
Advanced Natural Language Patterns
"How many times did [service] fail in the last [time period]?"
"Show me [severity] alerts for [service] [time range]"
"Count [alert name] incidents in [time period]"
"When was [service] down last [time period]?"
🤝 Contributing
Contributions welcome! Please ensure:
- TypeScript compilation passes (npm run build)
- Natural language query tests pass
- Documentation updated for new features
- Error handling comprehensive
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Built with ❤️ for DevOps and SRE teams who want smarter monitoring interactions
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