Provides persistent memory for AI agents, including context storage, facts, plans, RAG search, code snippets, and conversation compaction, enabling state to survive across sessions and processes.
Provides persistent memory for AI tools by building a local knowledge graph from conversations, enabling cross-session recall and context awareness without cloud dependencies.
Provides persistent local memory functionality for AI assistants, enabling them to store, retrieve, and search contextual information across conversations with SQLite-based full-text search. All data stays private on your machine while dramatically improving context retention and personalized assistance.
Provides persistent AI agent memory using a local vector database for long-term semantic storage and short-term session scratchpads. It enables low-latency memory operations including search, storage, and bulk management without external cloud dependencies.
Enables AI agents to automatically capture durable knowledge and retrieve only relevant, token-bounded context from a secure local-first long-term memory, with support for progressive disclosure, snapshots, health diagnostics, and background tasks.