MemOS
ActiveDescription
MemOS is a Memory Operating System for LLMs and AI agents that unifies store, retrieve, and manage for long-term memory, with built-in KB, multi-modal, and tool memory support.
Key Features
- Unified memory API for add, retrieve, edit, and delete — graph-structured, inspectable, not a black box
- Multi-modal memory supporting text, images, tool traces, and personas in one system
- Multi-Cube Knowledge Base management for isolated, shareable, composable memory across agents
- Memory feedback and correction via natural-language for continuous refinement over time
- Asynchronous ingestion via MemScheduler with millisecond-level latency at production scale
- +43.70% accuracy vs OpenAI Memory on benchmarks, saving 35.24% memory tokens
Use Cases
💡 Adding persistent long-term memory to AI agents and chatbots
💡 Building personalized AI assistants that remember user preferences across sessions
💡 Managing multi-agent memory sharing with knowledge base isolation
💡 Storing and retrieving tool usage history for agent planning and reasoning
Strengths & Limitations
✅ Strengths
- • Actively maintained, recent updates
- • High community interest (11.2k stars)
- • Permissive open-source license (Apache-2.0)
- • Responsive to issues, low backlog
Categories
Quick Start
Deploy via Docker or use the cloud service at memos-dashboard.openmem.net. Install the local plugin: `npm install @memtensor/memos-local-plugin`. For self-hosted: `docker compose up`. Use the unified API: `POST /memory/add`, `POST /memory/retrieve`, `POST /memory/edit`.