A-MEM
StaleDescription
An agentic memory system for LLM agents inspired by human memory mechanisms, enabling dynamic memory generation, retrieval, and consolidation with automatic memory evolution and self-organization.
An agentic memory system for LLM agents inspired by human memory mechanisms, enabling dynamic memory generation, retrieval, and consolidation with automatic memory evolution and self-organization.
A MemAgent framework that can extrapolate to 3.5M context tokens, along with a training framework for RL training of any agent workflow.
SimpleMem: Efficient Lifelong Memory for LLM Agents — supports text and multimodal memory for long-term information retention and retrieval.
An MCP server powered by Mem0 for long-term agent memory, supporting user preference memory, context-aware retrieval, and cross-session memory persistence, also useful as a Python MCP server development template.
Implementing cognitive architecture and psychological memory concepts into Agentic LLM Systems. Explores short-term, long-term, and working memory engineering for AI agents.