Enables AI assistants to have a living memory with atomic knowledge storage, multi-factor recall, organic decay, automatic learning, and graph traversal via MCP.
Causal graph memory engine for AI agents. Scores memories using relevance × connectivity × reactivation, connects them in a causal graph, and actively forgets irrelevant ones. 11 MCP tools
including store, recall, search, traverse, and explain.
A self-organizing, persistent semantic memory layer that enables AI agents to store, categorize, and retrieve information using hybrid vector and keyword search. It features autonomous chunking, deduplication, and hierarchical taxonomy management through a PostgreSQL-backed MCP server.
An intelligent memory MCP server that provides AI applications with semantic search, entity extraction, and knowledge graph capabilities using local Redis caching and optional cloud sync. It enables LLMs to store and retrieve long-term context across sessions with high-performance multi-tier storage.
A production-friendly memory platform with an MCP server interface, combining structured memory, semantic retrieval, knowledge graph operations, cross-session context, and safety controls.