AI Memory

Production-ready semantic memory management server that stores, retrieves, and manages contextual knowledge across sessions using PostgreSQL with pgvector for vector similarity search, featuring intelligent caching, multi-user support, memory relationships, automatic clustering, and background job processing for persistent AI memory and knowledge management systems.

Production-ready MCP server for semantic memory management that enables AI agents to store, retrieve, and manage contextual knowledge across sessions using PostgreSQL with pgvector for vector similarity search and local Transformers.js embeddings. Features intelligent caching with Redis fallback, multi-agent support through user context isolation, memory relationships for connected knowledge graphs, automatic clustering with DBSCAN algorithm, smart compression for large content, and background job processing with BullMQ for async embedding generation and batch operations. Built with TypeScript and Kysely ORM for type safety, it provides soft deletes, input sanitization, token-efficient responses, and flexible embedding dimensions, making it ideal for AI applications requiring persistent memory, knowledge management systems, and multi-session conversational agents.