AI-Powered Debugging

Find and fix bugs faster with intelligent error analysis, automated root cause detection, and AI-suggested solutions.

Debugging Capabilities

Error Analysis

Instant root cause detection

AI analyzes stack traces, identifies patterns, and pinpoints the exact cause of errors.

  • • Stack trace analysis
  • • Variable state inspection
  • • Execution flow tracking

Smart Suggestions

AI-powered fix recommendations

Get intelligent suggestions for fixing bugs based on code context and best practices.

  • • Multiple fix options
  • • Confidence scoring
  • • Impact analysis

Performance Profiling

Bottleneck detection

Identify performance issues and get optimization recommendations.

  • • CPU profiling
  • • Memory analysis
  • • Network monitoring

Anomaly Detection

Proactive issue identification

AI monitors your application and alerts you to potential issues before they become bugs.

  • • Pattern recognition
  • • Predictive analysis
  • • Early warning system

Error Analysis & Fixing

debug-error.js
// AI-Assisted Debugging
import { MCPDebugger } from '@mcpcodex/debug';

const debug = new MCPDebugger({
  model: 'claude-3-opus',
  verbosity: 'detailed'
});

// Automatic error analysis
debug.catch(async (error) => {
  // AI analyzes the error
  const analysis = await debug.analyze(error);
  
  console.log('Error Type:', analysis.type);
  console.log('Root Cause:', analysis.rootCause);
  console.log('Stack Analysis:', analysis.stackAnalysis);
  
  // AI suggests fixes
  const fixes = await debug.suggestFixes(error);
  fixes.forEach(fix => {
    console.log(`Fix ${fix.confidence}% confidence:`);
    console.log(fix.description);
    console.log(fix.code);
  });
  
  // AI checks for similar issues
  const similar = await debug.findSimilarIssues(error);
  console.log('Similar issues found:', similar.length);
});

// Intelligent breakpoints
debug.setSmartBreakpoint({
  condition: 'When user authentication fails',
  analyze: ['user', 'session', 'request'],
  trace: true
});

Performance Debugging

performance-debug.js
// Performance Debugging
import { MCPProfiler } from '@mcpcodex/debug';

const profiler = new MCPProfiler();

// AI identifies performance bottlenecks
async function processData(data: any[]) {
  const trace = profiler.start('processData');
  
  // Your code here
  const results = await complexOperation(data);
  
  // AI analyzes performance
  const analysis = trace.end();
  
  if (analysis.isBottleneck) {
    console.warn('Performance Issue Detected:');
    console.log('Duration:', analysis.duration, 'ms');
    console.log('Memory Delta:', analysis.memoryDelta, 'MB');
    
    // AI suggests optimizations
    const optimizations = await profiler.suggestOptimizations(
      'processData',
      analysis
    );
    
    optimizations.forEach(opt => {
      console.log(`Optimization: ${opt.impact} impact`);
      console.log(opt.description);
      console.log('Before:', opt.before);
      console.log('After:', opt.after);
    });
  }
  
  return results;
}

// AI monitors for memory leaks
profiler.watchMemoryLeaks({
  threshold: 100, // MB
  callback: (leak) => {
    console.error('Memory leak detected:', leak.location);
    console.log('Suggested fix:', leak.fix);
  }
});

Real-time Debugging

live-debug.js
// Real-time Debugging Interface
import { MCPLiveDebug } from '@mcpcodex/debug';

const liveDebug = new MCPLiveDebug({
  port: 9229,
  ui: true // Opens debugging UI
});

// Connect to running application
liveDebug.connect(process.pid);

// AI watches variable changes
liveDebug.watch('user.session', (oldVal, newVal) => {
  console.log('Session changed:', { oldVal, newVal });
  
  // AI detects anomalies
  if (liveDebug.isAnomaly(newVal)) {
    console.warn('Anomaly detected in session data');
    liveDebug.snapshot(); // Capture state
  }
});

// Interactive debugging with AI
liveDebug.on('breakpoint', async (context) => {
  // AI analyzes current state
  const state = await liveDebug.analyzeState(context);
  
  console.log('Current State Analysis:');
  console.log('Variables:', state.variables);
  console.log('Call Stack:', state.callStack);
  console.log('Predictions:', state.predictions);
  
  // AI suggests next debugging steps
  const nextSteps = await liveDebug.suggestNextSteps(context);
  console.log('Suggested actions:', nextSteps);
});

Debugging Techniques

Smart Breakpoints

Set conditional breakpoints using natural language. AI understands context like "break when user login fails" or "pause when memory exceeds 100MB".

Predictive Debugging

AI predicts potential issues before they occur by analyzing code patterns, data flow, and historical bug data.

Time-Travel Debugging

Record application state over time and replay execution to understand how bugs occurred. AI helps identify the exact moment things went wrong.

Collaborative Debugging

Share debugging sessions with team members. AI provides context and explanations to help everyone understand the issue.

Next Steps

Debug Smarter, Not Harder

Try our interactive debugging playground to see AI debugging in action.