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.
Persistent, semantically-searchable memory for AI agents using local PostgreSQL, pgvector, and Ollama embeddings, exposed via MCP with hybrid retrieval, knowledge graph, and auto-recall hook.
Local-first AI memory layer with hybrid retrieval and brain-inspired namespaces. Enables agents to save, search, and manage memories directly via MCP tools.
Persistent AI memory server with hybrid search and embedded sync. Enables AI agents to store, retrieve, and manage information across sessions with temporal knowledge graph support.
Persistent, auditable memory for AI agents. Hybrid BM25 + vector recall
with 18 MCP tools, adaptive block metadata (A-MEM), intent-aware routing,
contradiction detection, and governance workflows. Zero external
dependencies. Drop-in memory for Claude Code and any MCP-compatible agent.
