Sectional MCP Panel

# Sectional MCP Panel - Implementation Plan This document outlines the detailed implementation plan for the Sectional MCP Panel project, breaking down the development process into specific tasks with dependencies and sequence. ## Phase 1: Project Setup and Core Infrastructure ### 1.1 Development Environment Setup - Create project directory structure - Set up Python virtual environment - Install core dependencies (FastAPI, SQLite, Docker SDK, etc.) - Create basic Docker configuration for development - Set up version control ### 1.2 State Database Implementation - Design database schema for: - Panel configuration - Sections - Servers - Runtime state - Audit logs - Implement database initialization - Create database access layer - Implement basic CRUD operations - Add migration support for future schema changes ### 1.3 Configuration System Foundation - Define JSON schema for configuration - Implement configuration loading and parsing - Create validation logic - Implement hierarchical resolution (Global → Section → Server) - Add configuration persistence to database ## Phase 2: Core Engine Components ### 2.1 Runtime Engine Implementation - Implement Docker client integration - Create container management functions: - Container creation - Container start/stop - Resource limit application - Implement process execution fallback - Add status monitoring for running servers - Create logging capture mechanism ### 2.2 Orchestration Engine Implementation - Implement server lifecycle management: - Start/stop/restart individual servers - Status tracking - Create task queue for asynchronous operations - Implement concurrency control for group operations - Add section-level operations - Implement error handling and recovery ## Phase 3: API and Interface ### 3.1 API Layer Implementation - Set up FastAPI framework - Implement core API endpoints: - Section management (CRUD) - Server management (CRUD) - Server operations (start/stop/restart) - Section operations (start/stop/restart) - Status retrieval - Configuration management - Add request validation - Implement basic authentication (API key) - Add simple authorization - Create API documentation (Swagger/OpenAPI) ### 3.2 Web UI Development - Create basic HTML/CSS structure - Implement dashboard layout - Add section and server visualization - Create control interfaces (start/stop/restart) - Implement configuration editor - Add log viewer - Connect UI to API endpoints ## Phase 4: Integration and Testing ### 4.1 Component Integration - Connect all components: - API → Orchestration Engine - Orchestration Engine → Runtime Engine - Configuration System → All components - Implement end-to-end workflows - Add error handling across component boundaries ### 4.2 Testing - Create unit tests for critical components - Implement integration tests for workflows - Add test fixtures and mocks - Create test documentation ### 4.3 Deployment Packaging - Create Docker container for Panel service - Implement configuration for production deployment - Add startup/shutdown scripts - Create deployment documentation ## Phase 5: Documentation and Finalization ### 5.1 User Documentation - Create installation guide - Write user manual - Document API endpoints - Add configuration reference - Create troubleshooting guide ### 5.2 Final Testing and Refinement - Perform end-to-end testing - Fix identified issues - Optimize performance - Refine user interface - Ensure all documentation is complete ## Implementation Timeline (Estimated) - **Phase 1**: 1-2 weeks - **Phase 2**: 2-3 weeks - **Phase 3**: 2-3 weeks - **Phase 4**: 1-2 weeks - **Phase 5**: 1 week Total estimated time: 7-11 weeks for a complete implementation ## Dependencies and Requirements - Python 3.8+ - Docker Engine - SQLite (initial database) - FastAPI framework - Docker SDK for Python - Basic web development tools (HTML/CSS/JavaScript) ## Success Criteria The implementation will be considered successful when: 1. All core components are functioning as specified 2. The Panel can manage sections and servers through the API 3. Container-based server execution works reliably 4. The web UI provides basic management capabilities 5. Documentation is complete and accurate 6. The system can be deployed as a Docker container