bpftrace MCP Server

# MCPtrace Improvement Plan Based on comparison with GPTtrace, here's a prioritized roadmap to enhance MCPtrace: ## Phase 1: Core Feature Enhancements (2-3 weeks) ### 1. Example Database with Semantic Search - [ ] Create SQLite database for bpftrace examples - [ ] Implement vector embeddings using candle or ort - [ ] Add `search_examples` tool for finding relevant traces - [ ] Pre-populate with 50+ common tracing patterns ### 2. Program Validation & Safety - [ ] Add `validate_program` tool for pre-execution checks - [ ] Implement AST-based validation - [ ] Create safety rules engine - [ ] Add resource usage estimation ### 3. Enhanced Error Handling - [ ] Implement automatic retry with exponential backoff - [ ] Parse bpftrace errors into structured format - [ ] Add error categorization (syntax, permission, resource) - [ ] Provide AI-friendly error explanations ## Phase 2: Advanced Features (3-4 weeks) ### 4. Result Analysis Tools - [ ] Create `analyze_result` tool for structured output parsing - [ ] Add statistical analysis for numeric data - [ ] Implement pattern detection in trace outputs - [ ] Generate summaries and insights ### 5. Template System - [ ] Build template engine for common patterns - [ ] Create templates: syscall tracking, performance profiling, network monitoring - [ ] Add template customization parameters - [ ] Implement template composition ### 6. Interactive Features - [ ] Add `stop_execution` tool for running traces - [ ] Implement real-time output streaming - [ ] Create interactive parameter adjustment - [ ] Add execution progress monitoring ## Phase 3: Integration & Polish (2-3 weeks) ### 7. Knowledge Base - [ ] Create comprehensive probe documentation - [ ] Add kernel version compatibility matrix - [ ] Build troubleshooting guide - [ ] Include performance tuning tips ### 8. Advanced Query Features - [ ] Natural language to bpftrace translator - [ ] Query optimization suggestions - [ ] Multi-probe correlation support - [ ] Time-series data handling ### 9. Testing & Documentation - [ ] Comprehensive test suite - [ ] Integration tests with various kernel versions - [ ] Performance benchmarks - [ ] Migration guide from GPTtrace ## Quick Wins (Can start immediately) 1. **Add more descriptive tool responses** - Include execution statistics, warnings 2. **Implement basic templates** - Start with 5-10 most common patterns 3. **Create example catalog** - Even without search, a curated list helps 4. **Add execution metadata** - Timestamps, duration, resource usage ## Technical Implementation Notes - Maintain Rust's async architecture advantages - Keep MCP protocol compliance - Ensure backward compatibility - Focus on security and resource limits - Use existing crates where possible (sqlx, candle, serde) ## Success Metrics - Reduce average trace creation time by 50% - Achieve 90%+ first-attempt success rate - Support 100+ pre-built examples - Handle 95% of GPTtrace use cases - Maintain <100ms tool response time ## Migration Support - Create GPTtrace compatibility layer - Provide conversion scripts - Document feature mapping - Offer side-by-side comparison guide --- *See `doc/COMPARISON_WITH_GPTTRACE.md` and `doc/GPTTRACE_FEATURES_INTEGRATION.md` for detailed analysis and implementation examples.*