OpenChronicle captures macOS accessibility events to build structured local memory for LLM agents. Its async pipeline produces persistent Markdown memory and an SQLite index.
agentic-stack provides a harness-agnostic shared memory layer for AI coding agents, enabling seamless context persistence and migration across tools like Claude Code and Cursor.
OpenClaw Auto-Dream implements a 5-layer memory model with importance scoring and forgetting curves to consolidate AI agent memories like human sleep. It enables persistent, evolving knowledge.
A-MEM is a Python agentic memory system that dynamically organizes LLM agent memories using semantic embeddings and automatic linking, inspired by Zettelkasten.
