cloudwarriors-ai/pdb-debug

PDB Debug Gateway

A comprehensive REST API and MCP server for remote Python debugging using pdb.

🚀 Features

• Remote Debugging: Debug Python applications via REST API calls
• AI-Assisted Debugging: MCP server integration for Claude Code
• Session Management: Multiple concurrent debugging sessions
• Comprehensive Logging: Complete audit trail of debugging operations
• Multiple Breakpoint Types: Regular, conditional, and temporary breakpoints
• Variable Inspection: Real-time inspection of variables and expressions
• Step-by-Step Execution: Programmatic control over code execution flow

🎯 What This Enables

AI-Assisted Debugging

• Claude Code can automatically set breakpoints at suspicious code locations
• AI can step through execution to understand program flow
• Intelligent variable inspection to identify data corruption or logic errors
• Automated debugging reports with root cause analysis

Remote Debugging at Scale

• Debug production systems without direct server access
• Collaborative debugging with multiple developers
• Automated debugging pipelines integrated into CI/CD
• Cloud-native debugging for containerized applications

📁 Repository Structure

pdb-debug/
├── pdb-rest-gateway/          # Main PDB Gateway implementation
│   ├── src/pdb_gateway/       # Core library code
│   │   ├── api/              # REST API endpoints
│   │   ├── core/             # Debugging engine and session management
│   │   ├── mcp/              # MCP server implementation
│   │   └── schemas/          # Request/response schemas
│   ├── simple_server.py      # Standalone REST API server
│   ├── mcp_server.py         # MCP server for Claude Code
│   ├── requirements.txt      # Python dependencies
│   └── *.py                  # Test and demo scripts
├── breakpoint-simulation/     # Test applications and demos
│   ├── data_processor.py     # Sample data processing pipeline (295 lines)
│   ├── test_*.py            # Comprehensive test suites
│   └── *.md                 # Testing documentation
├── CLAUDE.md                 # Complete integration guide
└── README.md                # This file

🚀 Quick Start

1. Start the PDB Gateway Server

# REST API server (port 8002)
cd pdb-rest-gateway
python3 simple_server.py

# OR MCP server for Claude Code integration
python3 mcp_server.py

2. Test with Sample Application

# Run comprehensive debugging tests
python3 breakpoint-simulation/test_with_logging.py

# Test real debugging scenarios
python3 breakpoint-simulation/test_debugging.py

# Analyze debugging logs
python3 pdb-rest-gateway/view_logs.py

3. Debug Your Own Applications

# Create debug session via REST API
curl -X POST http://localhost:8002/debug/sessions \
  -H "Content-Type: application/json" \
  -d '{"target_file": "your_script.py"}'

# Set breakpoint
curl -X POST http://localhost:8002/debug/sessions/{session_id}/breakpoint \
  -H "Content-Type: application/json" \
  -d '{"filename": "your_script.py", "line_number": 25}'

# Step through execution
curl -X POST http://localhost:8002/debug/sessions/{session_id}/step \
  -H "Content-Type: application/json" \
  -d '{"step_type": "continue"}'

🔧 REST API Endpoints

🤖 MCP Tools for AI Assistants

When configured as an MCP server, provides these tools for Claude Code:

• pdb_start_session - Initialize debugging session
• pdb_set_breakpoint - Set/remove breakpoints
• pdb_step - Step through code execution
• pdb_inspect - Inspect variables and expressions
• pdb_execute - Execute arbitrary PDB commands
• pdb_list_sessions - List active sessions
• pdb_terminate_session - End debugging sessions

📊 Testing Results

Our comprehensive testing demonstrates:

• 47 operations executed in 0.817 seconds (57.5 ops/sec)
• 10 breakpoints set (regular, conditional, temporary)
• 8 step operations (next, continue, step with counts)
• 14 variable inspections (simple vars, complex expressions)
• 13 command executions (list, where, args, locals, etc.)
• Complete logging with 29.8 KB audit trail

🎯 Use Cases

Development & Debugging

• Interactive debugging of complex applications
• Root cause analysis of production issues
• Code behavior understanding and documentation
• Performance bottleneck identification

AI-Assisted Development

• Automated bug detection and analysis
• Intelligent code review and suggestions
• Educational code walkthroughs
• Debugging knowledge capture and sharing

Enterprise Applications

• Audit compliance with complete operation logging
• Security monitoring of debugging activities
• Collaborative debugging across teams
• Integration with CI/CD pipelines

📋 Requirements

• Python 3.7+
• Standard library modules (pdb, threading, json, etc.)
• Optional: FastAPI for REST server
• Optional: MCP library for Claude Code integration

🔍 Logging and Monitoring

All debugging operations are logged with:

• Timestamp tracking for all operations
• Success/failure status for each operation
• Complete parameter values and results
• Session duration and performance metrics
• Error tracking and debugging information

View logs with:

python3 pdb-rest-gateway/view_logs.py
tail -f pdb-rest-gateway/pdb_gateway.log

🚀 Future Possibilities

• Predictive debugging - AI predicts where bugs will occur
• Self-healing code - Systems that debug and fix themselves
• Intelligent monitoring - Continuous debugging of live systems
• Code optimization - AI suggests improvements based on execution analysis

📖 Documentation

See CLAUDE.md for complete integration guide including:

• ETL system integration examples
• Natural language debugging commands
• Comprehensive API documentation
• Troubleshooting and best practices

🎯 This tool revolutionizes Python debugging by making it programmable, remote, intelligent, and scalable!