o11y-mcp-server

poulsbopete/o11y-mcp-server
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Install to Claude Code

This server doesn't publish a one-line install command. Follow the setup in the source repository.

Summary

Connects to Elastic Agent Builder to enable AI-powered application health monitoring using OTEL metrics, traces, and logs from Elastic Serverless Observability.

README.md

🤖 Elastic Agent Builder Integration

Connect to Elastic Agent Builder for AI-powered application health monitoring using OTEL data from Elastic Serverless Observability.

✨ Features

  • AI-Powered Analysis through Elastic Agent Builder
  • Real-time Insights from OTEL metrics, traces, and logs
  • Built-in Tools for comprehensive monitoring
  • Easy Integration with Cursor IDE and other MCP clients
  • No Local Server Required - direct connection to Elastic

🎯 Available Agent Builder Tools

  • platform.core.search - Search OTEL data in Elasticsearch
  • platform.core.execute_esql - Execute ESQL queries on OTEL data
  • platform.core.generate_esql - Generate ESQL queries for analysis
  • Built-in Analysis - Error patterns, performance metrics, resource utilization
  • Real-time Monitoring - Application health, service dependencies, bottlenecks

🚀 Quick Start

Prerequisites

  • Elastic Serverless Observability endpoint with Agent Builder enabled
  • Valid API key for Elastic
  • Cursor IDE (optional, for MCP integration)

Installation

  1. Clone the repository
   git clone git@github.com:poulsbopete/o11y-mcp-server.git
   cd o11y-mcp-server
  1. Configure credentials
   # Option 1: Use setup script (recommended)
   ./setup-env.sh
   # Then edit .env file with your credentials
   
   # Option 2: Set environment variables
   export ELASTIC_ENDPOINT=https://your-endpoint.kb.us-east-1.aws.elastic.cloud
   export ELASTIC_API_KEY=your-api-key
  1. Connect to Agent Builder
   # Test Agent Builder connection
   ./connect-to-agent-builder.sh
   
   # Query application health
   ./query-application-health.sh
  1. Set up Cursor integration (optional)
   # Create Cursor MCP configuration
   ./setup-cursor-agent-builder.sh

🔗 Cursor Integration

Quick Setup

./setup-cursor-agent-builder.sh

Manual Setup

  1. Run the Cursor configuration script
  2. Restart Cursor IDE
  3. Connect to Elastic Agent Builder
  4. Ask questions like "What's the health of my applications?"

📊 Data Sources

Agent Builder connects to Elastic Serverless Observability and analyzes:

  • Metrics: metrics-* indices (CPU, memory, custom metrics)
  • Logs: logs-* indices (application logs, errors, events)
  • Traces: traces-* indices (distributed tracing data)

🛠️ Configuration

Environment Variables

  • ELASTIC_ENDPOINT - Your Elastic Serverless endpoint
  • ELASTIC_API_KEY - Your Elastic API key
  • LOG_LEVEL - Logging level (default: INFO)

Cursor MCP Configuration

The setup script creates ~/.cursor/mcp_config.json with Agent Builder integration.

📝 Example Queries

Once connected to Agent Builder, you can ask:

  • "What's the overall health of my applications?"
  • "Show me metrics for the payment service"
  • "What errors are happening in the last hour?"
  • "Find the slowest operations in my system"
  • "Analyze resource utilization across all services"
  • "Show me trace analysis for the checkout flow"
  • "Generate an ESQL query for error analysis"

🔧 Troubleshooting

Agent Builder Connection Issues

  • Verify Elastic endpoint and API key
  • Check if Agent Builder is enabled on your Elastic instance
  • Test connection: ./connect-to-agent-builder.sh

No Data Found

  • Check if applications are sending OTEL data
  • Verify time range includes recent data
  • Ensure proper Elastic cluster configuration

Cursor Integration Issues

  • Verify MCP configuration in Cursor settings
  • Check Agent Builder is accessible
  • Restart Cursor after configuration changes

📚 Documentation

  • CURSOR-MCP-INTEGRATION.md - Cursor integration guide
  • connect-to-agent-builder.sh - Agent Builder connection script
  • query-application-health.sh - Application health analysis script

🤝 Contributing

  1. Fork the repository
  2. Create a feature branch: git checkout -b feature-name
  3. Commit changes: git commit -am 'Add feature'
  4. Push to branch: git push origin feature-name
  5. Submit a pull request

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

🙏 Acknowledgments

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Ready to monitor your application health with AI-powered insights through Elastic Agent Builder! 🎉

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