MCP Software Engineer

# MCP Software Engineer - Architecture & WCGW Design ## Overview This MCP server has been completely refactored following the **WCGW (What Could Go Wrong)** engineering mindset. Every component assumes failure is inevitable and builds in safety, recovery, and observability. ## Core Principles ### 1. **Assume Everything Will Fail** - Every external call has timeouts - Every resource allocation is tracked - Every operation can be retried - Every error is recoverable ### 2. **Defense in Depth** - Input validation at multiple layers - Security checks before operations - Resource limits enforced - Circuit breakers for external services ### 3. **Observability First** - Structured logging with context - Metrics for every operation - Health checks and monitoring - Auto-recovery mechanisms ## Architecture Components ### Security Layer (`/src/config/security.ts`) **Purpose**: Prevent injection attacks, validate inputs, manage secrets **Key Features**: - Path traversal prevention - Command injection protection - Input sanitization - Rate limiting per tool - Encryption for sensitive data **WCGW Mitigations**: - Malicious file paths → Sanitized and validated - Command injection → Special characters stripped - DoS attacks → Rate limiting - Secret exposure → Encryption and redaction ### Configuration Management (`/src/config/index.ts`) **Purpose**: Centralized, validated, secure configuration **Key Features**: - Environment variable validation - Type-safe configuration access - Encrypted sensitive values - Safe defaults for everything **WCGW Mitigations**: - Missing config → Fail-safe defaults - Invalid values → Validation on load - Secret leakage → Automatic redaction in logs ### Logging System (`/src/utils/logger.ts`) **Purpose**: Structured, contextual, performance-aware logging **Key Features**: - Request ID tracking - User context preservation - Automatic PII redaction - Multiple output targets - Log rotation **WCGW Mitigations**: - Lost context → Request IDs throughout - Disk full → Log rotation - Performance impact → Async logging - Security leaks → Automatic sanitization ### Resource Management (`/src/utils/resource-manager.ts`) **Purpose**: Prevent resource leaks and exhaustion **Key Features**: - Process lifecycle management - Connection pooling - File handle tracking - Memory monitoring - Automatic cleanup **WCGW Mitigations**: - Memory leaks → Tracked allocations - File descriptor exhaustion → Limited handles - Zombie processes → Automatic termination - Connection leaks → Pool management ### Error Handling (`/src/utils/errors.ts`) **Purpose**: Consistent, recoverable error handling **Key Features**: - Typed error hierarchy - Operational vs programmer errors - Retry strategies - Circuit breaker pattern - Error context preservation **WCGW Mitigations**: - Cascading failures → Circuit breakers - Transient errors → Automatic retry - Lost context → Error chain preservation - Silent failures → Forced handling ### Base Tool Framework (`/src/tools/base-tool.ts`) **Purpose**: Consistent safety layer for all tools **Key Features**: - Input validation (Zod schemas) - Output validation - Execution timeouts - Metric collection - Error standardization **Tool Types**: - `BaseTool`: Core functionality - `FileBasedTool`: File operations with size limits - `DatabaseTool`: Connection pooling, transactions **WCGW Mitigations**: - Invalid inputs → Schema validation - Infinite execution → Timeouts - Resource exhaustion → Limits enforced - Performance issues → Automatic metrics ### Monitoring System (`/src/monitoring/metrics.ts`) **Purpose**: Real-time performance and health tracking **Key Features**: - Counter, gauge, histogram metrics - Operation performance tracking - System resource monitoring - Threshold-based alerts - Percentile calculations **Metrics Collected**: - Request latencies (p50, p90, p99) - Error rates by operation - Memory usage trends - CPU utilization - Event loop lag **WCGW Mitigations**: - Performance degradation → Early detection - Memory leaks → Trend analysis - System overload → Real-time alerts ### Auto-Recovery System (`/src/monitoring/auto-recovery.ts`) **Purpose**: Automatic detection and recovery from failures **Key Features**: - Memory leak detection - Garbage collection triggers - Resource cleanup - Graceful degradation - Automatic restarts **Recovery Strategies**: 1. **Memory Pressure**: - Trigger GC at 70% usage - Aggressive cleanup at 90% - Restart at 95% 2. **Event Loop Blocking**: - Detect delays > 100ms - Alert on > 5s blocks - Recovery for > 10s blocks 3. **High Error Rates**: - Circuit breaker activation - Backpressure implementation - Gradual recovery **WCGW Mitigations**: - Memory exhaustion → Proactive GC - Deadlocks → Timeout and recovery - Cascade failures → Circuit breakers - Resource leaks → Periodic cleanup ## Security Considerations ### Input Validation - All inputs validated against Zod schemas - Path traversal prevention - SQL injection protection - Command injection blocking - Size limits on all operations ### Authentication & Authorization - JWT token validation - Rate limiting per user/tool - Audit logging for security events - Encrypted sensitive data ### Safe Defaults - Minimal permissions - Timeouts on everything - Conservative resource limits - Fail-closed behavior ## Performance Optimizations ### Connection Pooling - Database connections reused - Configurable pool sizes - Health checks on connections - Automatic cleanup ### Caching Strategy - In-memory caches with TTL - Size-limited caches - Cache invalidation hooks - Metrics on hit/miss rates ### Async Everything - Non-blocking I/O - Parallel operations where safe - Queue management for heavy ops - Backpressure support ## Operational Readiness ### Health Checks - `/health` endpoint (when HTTP enabled) - Database connectivity - Resource usage - Tool availability ### Metrics & Monitoring - Prometheus-compatible metrics - Structured JSON logs - Performance tracking - Error rate monitoring ### Debugging Support - Request tracing - Detailed error messages - Performance profiling - Resource usage tracking ## Failure Scenarios Handled 1. **Memory Exhaustion** - Detection via monitoring - GC triggering - Cache clearing - Graceful restart 2. **Database Failures** - Connection pool retry - Transaction rollback - Circuit breaker activation - Fallback responses 3. **File System Issues** - Path validation - Size limits - Backup creation - Atomic operations 4. **External Service Failures** - Timeouts enforced - Retry with backoff - Circuit breakers - Graceful degradation 5. **Malicious Input** - Input sanitization - Query parameterization - Path traversal blocking - Rate limiting ## Testing Strategy ### Unit Tests - Tool validation logic - Security functions - Error handling paths - Resource management ### Integration Tests - Database operations - File system operations - External API calls - Full request flow ### Stress Tests - Concurrent operations - Memory pressure - Large file handling - Sustained load ### Security Tests - Injection attempts - Path traversal - Resource exhaustion - Rate limit bypass ## Deployment Considerations ### Environment Variables ```bash NODE_ENV=production LOG_LEVEL=info MAX_MEMORY_MB=512 RATE_LIMIT_WINDOW_MS=60000 RATE_LIMIT_MAX_REQUESTS=100 ``` ### Resource Requirements - Memory: 512MB minimum - CPU: 1 core minimum - Disk: 1GB for logs/temp - Network: Outbound for APIs ### Monitoring Setup 1. Log aggregation (ELK, Datadog) 2. Metric collection (Prometheus) 3. Alert configuration 4. Dashboard creation ## Future Improvements 1. **Distributed Tracing** - OpenTelemetry integration - Request flow visualization - Performance bottleneck identification 2. **Advanced Caching** - Redis integration - Distributed cache - Smart invalidation 3. **Machine Learning** - Anomaly detection - Predictive scaling - Smart retries 4. **Enhanced Security** - OAuth2 integration - API key management - Audit log analysis ## Conclusion This architecture prioritizes **reliability**, **security**, and **observability**. Every component assumes failure and builds in recovery. The WCGW mindset ensures the system can handle real-world conditions including malicious input, resource exhaustion, and cascading failures. The result is a production-ready MCP server that can be trusted with critical operations while maintaining excellent debugging and operational characteristics.