Memory PostgreSQL
Provides long-term memory capabilities using PostgreSQL with pgvector for efficient semantic search across stored memories, enabling tagging, confidence scoring, and filtering for maintaining context across conversations.
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MCP Memory Server provides long-term memory capabilities for AI assistants using PostgreSQL with pgvector for efficient vector similarity search. The implementation uses the Xenova/all-MiniLM-L6-v2 model to automatically generate embeddings for stored memories, enabling semantic search across different memory types. It exposes tools for creating, searching, and listing memories with support for tagging, confidence scoring, and filtering, making it particularly valuable for AI assistants that need to maintain context and recall information across conversations without losing important details.
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