Awesome AI Memory | LLM Memory | A curated knowledge base on AI memory for LLMs and agents, covering long-term memory, reasoning, retrieval, and memory-native system design. Awesome-AI-Memory 是一个 集中式、持续更新的 AI 记忆知识库，系统性整理了与 大模型记忆（LLM Memory）与智能体记忆（Agent Memory） 相关的前沿研究、工程框架、系统设计、评测基准与真实应用实践。

Lightweight Long-Term Memory for LLM Agents.

Automatic memory for OpenCode agents: persistent workspace memory, hot session context, and compaction-based memory extraction — with zero extra API calls.

Turns AI coding tools into reliable software delivery systems. Drop a .gaai/ folder into any project — Discovery defines what to build, Delivery executes autonomously until criteria pass. Works with Claude Code, Codex CLI, Gemini CLI, Cursor, and more. No SDK. No package. Markdown + YAML + bash.

A guide to building persistent AI memory using Obsidian, so your AI assistant knows you without re-explaining yourself every session

AI memory system combining vector search with temporal knowledge graph. Built-in cognitive engine for agents. Supports memory decay, contradiction detection, and MCP integration.

POC visual search with smart glasses and Qdrant Edge.

Lightweight, local-first memory for AI agents. Hybrid vector + BM25 search, LLM-powered fact extraction, zero infrastructure — just pip install.

Repo-local continuity runtime for AI coding agents. Helps them continue from the same inspectable work state instead of starting cold. Stop onboarding your coding agents like rookies every session.

A lightweight persistent-memory companion for OpenCode & Claude

Recallium is a local, self-hosted universal AI memory system providing a persistent knowledge layer for developer tools (Copilot, Cursor, Claude Desktop). It eliminates "AI amnesia" by automatically capturing, clustering, and surfacing decisions and patterns across all projects. It uses the MCP for universal compatibility and ensures privacy

Helix-AGI is an Agentic AI System that uses an 8d spatial-graph memory retrieval system. Agents receive a rolling adaptive system prompt of memories and skills that afford the agent a highly dynamic center of conceptual gravity. By avoiding long identity files and subagent-heavy workflows, Agents can develop continuously without spiraling costs.

A persistent AI entity harness. The entity has its own identity files, a memory hierarchy that consolidates across time, and a single canonical self that persists across multiple interfaces.

Mimir's Memory Hub - multi-agent AI chat with persistent memory and SillyTavern compatibility

The World's #1 Memory Architecture for AI • Memory that thinks, learns, and dreams • Synthetic cognition infrastructure for Agentic Ai.

Persistent context for any AI agent with rules that hold themselves.

Context and memory management for agents to learn over time. Private and lightweight.

A local MCP server that provides a vector file store to give AI agents a long-term memory.

Local-first agent memory in one SQLite file: sqlite-vec/QJL two-pass vector + FTS5 search, knowledge graph (optional auto capture,) Ed25519-signed entries, and MCP server. No cloud dependencies.