Semantic Memory System
Provides persistent semantic memory capabilities through PostgreSQL with pgvector embeddings, enabling project-based memory namespacing, semantic search, and relationship management for building connected knowledge graphs across conversations.
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An agentic semantic memory system MCP server by Tristan McInnis that provides persistent memory capabilities for Claude Code through PostgreSQL with pgvector embeddings. The implementation supports project-based memory namespacing, semantic search using either simple local embeddings or Llama models, and memory relationship management for building connected knowledge graphs. Built with TypeScript, Drizzle ORM, and Neon database integration, it enables AI assistants to store, retrieve, and relate contextual information across conversations and projects, making it valuable for maintaining long-term context, building knowledge bases, and creating more intelligent conversational workflows.
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