A lightweight MCP server that provides long-term memory for LLMs by storing and retrieving important facts, decisions, and preferences through smart semantic search and automatic organization.
MCP server that enables persistent, hybrid, local memory for LLM agents, with vector + BM25 search, knowledge graph, and policy-driven retention, providing token-budgeted context injection for AI assistants.
A universal MCP server providing persistent, structured memory through a knowledge graph with graph storage, semantic vector search, and multi-hop traversal for AI agents and IDEs.
MCP server that gives AI agents and teams persistent, shared memory using a knowledge graph with vector embeddings, automatic consolidation of related facts, and hybrid search.
MCP server providing persistent AI memory with four-tier retrieval (SQLite FTS5, graph, vector, LLM agent) to give AI assistants structured, long-term memory without RAG.
Open-source MCP server that gives any LLM long-term memory using a knowledge graph and vector search hybrid. It stores entities, observations, and relationships, enabling semantic recall across sessions with automatic clustering and fail-loud infrastructure.