mcp-adr-analysis-server

# ADR-003: Memory-Centric Architecture ## Status Accepted ## Context The MCP ADR Analysis Server requires persistent storage and retrieval of architectural knowledge, analysis results, and learning experiences. Based on the project analysis and memories, the system implements a sophisticated memory system with knowledge graphs, entity storage, and intelligent querying capabilities. This architecture needs to support both short-term caching and long-term knowledge retention. ## Decision We will implement a memory-centric architecture using JSON-based storage with knowledge graph capabilities, entity relationship management, and intelligent memory retrieval systems. Key components: - **Knowledge Graph Storage**: Structured storage of architectural decisions and relationships - **Entity Management**: Persistent storage of analysis entities with metadata - **Intelligent Querying**: Context-aware memory retrieval with relevance scoring - **Cache Infrastructure**: Multi-layer caching for performance optimization - **Memory Integration**: Seamless integration across all MCP tools - **Snapshot System**: Historical tracking of architectural evolution ## Consequences **Positive:** - Persistent knowledge retention across analysis sessions - Intelligent context-aware retrieval of relevant past experiences - Knowledge graph enables relationship discovery and pattern recognition - Performance optimization through multi-layer caching - Historical tracking enables architectural evolution analysis - Seamless integration provides consistent memory access across tools **Negative:** - Increased storage requirements for comprehensive memory retention - Complexity in managing entity relationships and knowledge graph consistency - Potential performance impact from memory operations during analysis - Need for sophisticated cache invalidation and consistency management - Risk of memory corruption affecting analysis quality - Dependency on file system reliability for persistent storage