Observability Dashboard Analyzer

Production-ready MCP Server for intelligent Loki log analysis and Grafana dashboard generation based on industry-standard monitoring methodologies (RED Method).

🎯 Key Features

• Smart Analysis: Analyzes Loki logs to recommend optimal dashboard configurations
• RED Method Implementation: Industry-standard Rate, Errors, Duration monitoring dashboards
• Service Discovery: Automatic detection of services from log data
• Query Optimization: Performance optimization suggestions for LogQL queries
• Production Ready: Handles authentication, errors, and enterprise deployment scenarios

🚀 Quick Start

Installation

npm install -g observability-dashboard-analyzer

Configuration

The tool uses multi-tier configuration (environment variables > config file > defaults):

1. Environment Variables (highest priority):

   export LOKI_URL=http://localhost:3100
   export LOKI_USERNAME=your-username
   export LOKI_PASSWORD=your-password

2. Config File (medium priority): Edit ~/.observability-analyzer/config.json:

   {
     "loki": {
       "url": "http://localhost:3100",
       "auth": {
         "type": "basic",
         "username": "your-username",
         "password": "your-password"
       }
     }
   }

Usage with Claude Desktop

Add to your Claude Desktop MCP configuration:

{
  "mcpServers": {
    "observability-analyzer": {
      "command": "npx",
      "args": ["observability-dashboard-analyzer"]
    }
  }
}

🔧 MCP Tools

Core Analysis Tools

analyze_loki_stack

Analyzes your Loki setup and discovers services with log structure analysis.

// Example usage in Claude
"Analyze my Loki logs for the last 24 hours"

Returns:

• Service discovery from log data
• Log structure quality assessment
• Available labels and error patterns
• Dashboard recommendations based on data structure

generate_loki_dashboard

Creates production-ready Loki monitoring dashboard with service-specific panels.

"Generate a dashboard for my payment-api and user-service"

Features:

• Log volume monitoring by service
• Error rate tracking with thresholds
• Log level distribution analysis
• Service health overview
• Error pattern detection

validate_loki_queries

Tests LogQL queries against real Loki API to validate query performance.

"Validate these LogQL queries for performance"

Features:

• Query syntax validation
• Performance optimization suggestions
• Success rate analysis
• Query execution testing

export_loki_dashboard

Exports Loki dashboard to Grafana-compatible JSON file.

"Export dashboard for my services to a JSON file"

Features:

• Grafana-compatible JSON export
• Service-specific configurations
• Optimized LogQL queries
• Production-ready dashboard structure

🏗️ Architecture

Research-Driven Design

The tool implements monitoring methodologies based on industry research:

• RED Method (Request rate, Error rate, Duration) - Universal microservices standard
• Service Discovery - Automatic detection from log labels and content
• Log Structure Analysis - Quality assessment for dashboard feasibility

Log Analysis Algorithm

Dashboards are recommended based on log data analysis:

• Service Discovery: Automatic detection from service labels and JSON content
• Log Structure Quality: Assessment of structured logs and error patterns
• Volume Analysis: Log throughput and service activity measurement

Query Optimization

The tool provides performance optimization suggestions:

• LogQL Optimization: Avoid regex wildcards, use exact string matching first
• Label Filtering: Use specific label selectors for better performance
• Query Patterns: Efficient time-based and service-based queries

🔒 Security & Authentication

Supports authentication methods:

• Basic Auth: Username/password authentication (most common)
• No Auth: For local development setups

📊 Dashboard Features

Generated Dashboard Includes:

1. Log Volume Monitoring

   • Service-based log volume tracking
   • Request rate analysis from log data
   • Time-based volume patterns

2. Error Rate Tracking

   • Error detection from log patterns
   • Industry-standard thresholds (1% yellow, 5% red)
   • Error pattern analysis

3. Service Health Overview

   • Multi-service comparison
   • Log level distribution
   • Service activity monitoring

🧪 Testing

Run the comprehensive test suite:

# Run all tests
npm test

# Run with coverage
npm run test:coverage

# Run specific test suites
npm test -- red-method.test.ts

Test Coverage:

• Unit tests for dashboard generators
• Integration tests with mocked Loki APIs
• Query validation and optimization testing
• Configuration and authentication testing

🚀 Development

Project Structure

src/
├── index.ts                    # MCP server entry point
├── config/
│   ├── ConfigManager.ts       # Multi-tier configuration
│   └── AuthHandler.ts         # Authentication handling
├── analyzers/
│   └── LokiAnalyzer.ts        # LogQL query generation & analysis
├── dashboards/
│   ├── REDMethodGenerator.ts   # RED method dashboards
│   └── GrafanaExporter.ts     # Dashboard export utilities
├── types/
│   ├── loki-api.ts            # Loki API types
│   ├── grafana-config.ts      # Grafana dashboard types
│   ├── monitoring-methods.ts  # Monitoring methodology types
│   └── config.ts              # Configuration types
└── __tests__/                 # Test suite

Building

npm run build      # TypeScript compilation
npm run lint       # ESLint checking
npm run typecheck  # TypeScript type checking

📈 Success Metrics

• Functional: Generates working dashboards for common Loki setups
• Performance: Analyzes Loki logs in <30 seconds
• Usability: npm install -g → working in Claude within 5 minutes
• Professional: 90%+ test coverage + comprehensive TypeScript types

🤝 Contributing

1. Fork the repository
2. Create a feature branch: git checkout -b feature/amazing-feature
3. Run tests: npm test
4. Commit changes: git commit -m 'Add amazing feature'
5. Push to branch: git push origin feature/amazing-feature
6. Open a Pull Request

📄 License

MIT License - see LICENSE file for details.

🔗 Links

• RED Method Documentation
• Loki Documentation
• LogQL Documentation

Built for production observability teams who need immediate value from their Loki setup. 🚀