documcp

--- id: README title: Architectural Decision Records sidebar_label: ADR Overview sidebar_position: 1 --- # Architectural Decision Records (ADRs) This directory contains the Architectural Decision Records for the DocuMCP project - an intelligent MCP server for GitHub Pages documentation deployment. ## ADR Index | ADR | Title | Status | Date | Summary | |-----|-------|--------|------|---------| | [001](001-mcp-server-architecture.md) | MCP Server Architecture using TypeScript SDK | Accepted | 2025-01-14 | Core server architecture decision using TypeScript MCP SDK with modular, stateless design | | [002](002-repository-analysis-engine.md) | Multi-Layered Repository Analysis Engine Design | Accepted | 2025-01-14 | Comprehensive repository analysis through multiple layers: file system, language ecosystem, content, metadata, and complexity assessment | | [003](003-static-site-generator-recommendation-engine.md) | Static Site Generator Recommendation Engine Design | Accepted | 2025-01-14 | Multi-criteria decision analysis framework for intelligent SSG recommendations with confidence scoring | | [004](004-diataxis-framework-integration.md) | Diataxis Framework Integration for Documentation Structure | Accepted | 2025-01-14 | Integration of Diataxis framework as foundational information architecture for all generated documentation | | [005](005-github-pages-deployment-automation.md) | GitHub Pages Deployment Automation Architecture | Accepted | 2025-01-14 | Comprehensive deployment orchestration with SSG-specific workflows, security best practices, and performance optimization | | [006](006-mcp-tools-api-design.md) | MCP Tools API Design and Interface Specification | Accepted | 2025-01-14 | Six core MCP tools providing comprehensive documentation workflow coverage with robust validation and error handling | | [007](007-mcp-prompts-and-resources-integration.md) | MCP Prompts and Resources Integration for AI Assistance | Proposed | 2025-01-14 | Native MCP prompts and resources for guided workflows and content access, leveraging built-in protocol capabilities | | [008](008-intelligent-content-population-engine.md) | Intelligent Content Population Engine for Diataxis Documentation | Proposed | 2025-01-23 | Project-aware content generation engine that transforms repository analysis into contextually relevant Diataxis documentation | | [009](009-content-accuracy-validation-framework.md) | Content Accuracy and Validation Framework for Generated Documentation | Proposed | 2025-01-23 | Comprehensive accuracy assurance system with confidence scoring, reality-check validation, and interactive correction workflows | ## ADR Process This project follows the Architectural Decision Record (ADR) process as defined by Michael Nygard. Each ADR documents a significant architectural decision made during the project's development. ### ADR Template Each ADR follows a consistent structure: - **Status**: Proposed, Accepted, Deprecated, or Superseded - **Context**: The situation and requirements that led to the decision - **Decision**: The actual architectural decision made - **Alternatives Considered**: Other options that were evaluated - **Consequences**: Positive and negative outcomes of the decision - **Implementation Details**: Technical specifics and code examples where relevant ### Decision Categories Our ADRs are organized into the following categories: #### Foundation Architecture (ADRs 001-002) - Core server architecture and technology choices - Repository analysis engine design #### Intelligence & Recommendation (ADRs 003) - Static site generator recommendation algorithms - Decision-making frameworks #### Content & Structure (ADRs 004, 008, 009) - Documentation framework integration - Information architecture decisions - Intelligent content population and generation - Content accuracy and validation frameworks #### Deployment & Integration (ADRs 005-006) - GitHub Pages deployment automation - MCP tools API design #### AI & Assistance (ADR 007) - MCP prompts and resources for guided workflows ## Key Architectural Principles Based on our ADRs, DocuMCP follows these core architectural principles: ### 1. **Methodological Pragmatism** - Evidence-based decision making with explicit confidence scoring - Systematic verification processes for all recommendations - Clear acknowledgment of limitations and uncertainty ### 2. **Standards Compliance** - Full adherence to MCP specification requirements - Industry best practices for static site generation - Proven frameworks like Diataxis for information architecture ### 3. **Modular Design** - Clear separation of concerns between analysis, recommendation, generation, and deployment - Extensible architecture supporting future enhancements - Stateless operation for consistency and reliability ### 4. **Intelligent Automation** - Deep repository analysis for informed decision making - Context-aware configuration generation - Performance-optimized deployment workflows ### 5. **Developer Experience** - Intuitive MCP tools API with comprehensive validation - Clear error messages and troubleshooting guidance - Progressive complexity from simple to advanced use cases ## Decision Timeline The ADRs were developed during the planning phase of DocuMCP, establishing the architectural foundation before implementation. The decisions build upon each other: 1. **Foundation** (ADR-001): Established TypeScript/MCP SDK as the core platform 2. **Analysis** (ADR-002): Defined multi-layered repository analysis approach 3. **Intelligence** (ADR-003): Specified recommendation engine architecture 4. **Structure** (ADR-004): Integrated Diataxis framework for quality documentation 5. **Deployment** (ADR-005): Designed automated GitHub Pages deployment system 6. **Interface** (ADR-006): Specified comprehensive MCP tools API ## Confidence and Validation Each ADR includes confidence assessments and validation strategies: - **High Confidence Decisions**: Technology choices with strong ecosystem support (TypeScript/MCP SDK) - **Medium Confidence Decisions**: Framework integrations with proven track records (Diataxis) - **Validated Assumptions**: Architectural patterns tested through prototype development - **Risk Mitigation**: Explicit identification and mitigation strategies for each decision ## Future Considerations Our ADRs acknowledge areas for future evolution: - **Machine Learning Integration**: Potential for AI-powered content analysis and recommendations - **Performance Optimization**: WebAssembly modules for intensive analysis operations - **Extended SSG Support**: Community-contributed static site generator profiles - **Advanced Deployment**: Multi-environment and blue-green deployment capabilities ## References - [Architectural Decision Records](https://adr.github.io/) - [Model Context Protocol Specification](https://spec.modelcontextprotocol.io/) - [Diataxis Framework](https://diataxis.fr/) - [Static Site Generator Analysis](https://jamstack.org/generators/) --- **Last Updated**: January 23, 2025 **Total ADRs**: 9 **Status**: ADRs 001-006 Accepted and Implemented, ADRs 007-009 Proposed