EGH Research

# EGW Writings MCP Server - Implementation Plan ## Project Overview Creating an MCP server for Ellen G. White writings and Adventist literature to provide contextual AI research assistance. **Repository**: https://github.com/Surgbc/egw-writings-mcp **Status**: Phase 1 - Data Extraction ## Phase 1: Data Extraction (2-3 days) ### 1.1 APK Analysis - [x] Research APK download and extraction methods (apktool, unzip) - [ ] Download EGW Writings Android app from APKMirror/APKPure - [ ] Extract APK using `apktool` or `unzip` - [ ] Analyze app structure for API endpoints - [ ] Document network requests and data formats **Tools Identified:** - APKMirror/APKPure for APK downloads - `apktool` for reverse engineering - `unzip` for basic extraction - Network analysis for API discovery ### 1.2 API Reverse Engineering - [ ] Identify book listing endpoints - [ ] Identify chapter/paragraph retrieval endpoints - [ ] Document authentication requirements (if any) - [ ] Test API endpoints for data access - [ ] Map data structure and response formats ### 1.3 Data Collection Pipeline - [ ] Implement book metadata collection - [ ] Implement paragraph-level content extraction - [ ] Handle rate limiting and respectful scraping - [ ] Validate data integrity and completeness - [ ] Organize by categories (Ellen White, Pioneers, Commentaries) ## Phase 2: Data Processing and Storage (3-4 days) ### 2.1 Database Design - [ ] Design SQLite schema for books, chapters, paragraphs - [ ] Implement FTS5 full-text search indexing - [ ] Add metadata for book categories - [ ] Create efficient query structures for AI context ### 2.2 Data Processing - [ ] Clean and normalize extracted text - [ ] Parse paragraph identifiers (e.g., "GC 415.2") - [ ] Build cross-reference indexes - [ ] Implement search optimization for fast retrieval ### 2.3 Storage Strategy - **Raw Data**: JSON files for each book/chapter - **Processed Data**: SQLite database with optimized schema - **Search Index**: FTS5 virtual tables for fast text search - **Metadata**: Book hierarchies, categories, cross-references ## Phase 3: MCP Server Implementation (2-3 days) ### 3.1 Core MCP Server - [ ] Implement MCP protocol handlers - [ ] Create resource discovery endpoints - [ ] Add tool registration and capabilities - [ ] Implement error handling and logging ### 3.2 Search Tools - [ ] Full-text search across all writings - [ ] Category-specific search (Ellen White, Pioneers, etc.) - [ ] Citation and reference lookup (e.g., "GC 415.2") - [ ] Context window optimization for AI consumption ### 3.3 Context Tools - [ ] Paragraph retrieval by identifier - [ ] Book chapter summaries - [ ] Related content suggestions - [ ] Quote verification and attribution ## Phase 4: Testing and Deployment (1-2 days) ### 4.1 Testing - [ ] Unit tests for data extraction - [ ] Integration tests for MCP server - [ ] Performance testing for search queries - [ ] Validation of data accuracy ### 4.2 Documentation - [ ] API documentation for MCP tools - [ ] Usage examples and guides - [ ] Data source attributions - [ ] Deployment instructions ## Technical Stack ### Development - **Runtime**: Node.js 18+ with TypeScript - **Database**: SQLite with FTS5 full-text search - **MCP Framework**: @modelcontextprotocol/sdk - **HTTP Client**: axios for API requests - **Build Tools**: tsx, eslint, jest ### APK Analysis - **Primary**: `apktool` for reverse engineering - **Alternative**: `unzip` for basic extraction - **Network Analysis**: Monitor app traffic for API discovery - **Static Analysis**: Examine code for hardcoded endpoints ### Data Pipeline - **Extraction**: Respectful scraping with rate limiting - **Processing**: Text normalization and indexing - **Storage**: SQLite with optimized schema - **Search**: FTS5 + custom indexing for fast queries ## Current Status ### Completed ✅ 1. Project structure and README created 2. Package.json with dependencies defined 3. TypeScript configuration 4. Git repository initialized 5. Private GitHub repository created 6. APK analysis tools researched ### Next Steps 🔄 1. Download EGW Writings APK 2. Extract and analyze for API endpoints 3. Test API endpoints and document formats 4. Begin data collection pipeline ## Data Source Strategy **Primary Source**: egwwritings.org Android app - Extract API endpoints from app - Reverse engineer data access methods - Document request/response formats - Implement respectful data collection **Data Categories**: - Ellen G. White writings - Pioneer writings - Commentaries and related literature - Organized by books with paragraph identifiers ## Ethical Considerations - Respectful rate limiting to avoid server overload - Proper attribution of all content sources - Compliance with egwwritings.org terms of service - Educational and research use focus - No redistribution beyond fair use ## Success Metrics 1. **Data Coverage**: Complete extraction of available writings 2. **Search Performance**: Sub-100ms search responses 3. **MCP Integration**: Seamless AI assistant integration 4. **Data Accuracy**: Verified paragraph identifiers and content 5. **Usability**: Clear documentation and examples ## Risk Mitigation - **API Changes**: Document multiple extraction methods - **Rate Limiting**: Implement respectful delays and retry logic - **Data Quality**: Validation and integrity checks - **Legal Compliance**: Educational use and proper attribution - **Performance**: Optimized indexing and caching strategies --- *Plan created: 2025-07-13* *Last updated: 2025-07-13*