MemTensor / MemOS

MemOS 2.0: 星尘（Stardust） 🎯 +43.70% Accuracy vs. OpenAI Memory 🏆 Top-tier long-term memory + personalization 💰 Saves 35.24% memory tokens LoCoMo 75.80 • LongMemEval +40.43% • PrefEval-10 +2568% • PersonaMem +40.75% --> --> 🦞 Enhanced OpenClaw with MemOS Plugin 🦞 Your lobster now has a working memory system — choose **Cloud** or **Local** to get started. ☁️ Cloud Plugin — Hosted Memory Service • **72% lower token usage** — intelligent memory retrieval instead of loading full chat history • **Multi-agent memory sharing** — multi-instance agents share memory via same user_id, automatic context handoff Get your API key: MemOS Dashboard Full tutorial → MemOS-Cloud-OpenClaw-Plugin 🧠 Local Plugin — 100% On-Device Memory • **Zero cloud dependency** — all data stays on your machine, persistent local SQLite storage • **Hybrid search + task & skill evolution** — FTS5 + vector search, auto task summarization, reusable skills that self-upgrade • **Multi-agent collaboration + Memory Viewer** — memory isolation, skill sharing, full web dashboard with 7 management pages 🌐 Homepage · 📖 Documentation · 📦 NPM 📌 MemOS: Memory Operating System for AI Agents **MemOS** is a Memory Operating System for LLMs and AI agents that unifies **store / retrieve / manage** for long-term memory, enabling **context-aware and personalized** interactions with **KB**, **multi-modal**, **tool memory**, and **enterprise-grade** optimizations built in. Key Features • **Unified Memory API**: A single API to add, retrieve, edit, and delete memory—structured as a graph, inspectable and editable by design, not a black-box embedding store. • **Multi-Modal Memory**: Natively supports text, images, tool traces, and personas, retrieved and reasoned together in one memory system. • **Multi-Cube Knowledge Base Management**: Manage multiple knowledge bases as composable memory cubes, enabling isolation, controlled sharing, and dynamic composition across users, projects, and agents. • **Asynchronous Ingestion via MemScheduler**: Run memory operations asynchronously with millisecond-level latency for production stability under high concurrency. • **Memory Feedback & Correction**: Refine memory with natural-language feedback—correcting, supplementing, or replacing existing memories over time. News • **2026-03-08** · 🦞 **MemOS OpenClaw Plugin — Cloud & Local** Official OpenClaw memory plugins launched. **Cloud Plugin**: hosted memory service with 72% lower token usage and multi-agent memory sharing (MemOS-Cloud-OpenClaw-Plugin). **Local Plugin** ( ): 100% on-device memory with persistent SQLite, hybrid search (FTS5 + vector), task summarization & skill evolution, multi-agent collaboration, and a full Memory Viewer dashboard. • **2025-12-24** · 🎉 **MemOS v2.0: Stardust (星尘) Release** Comprehensive KB (doc/URL parsing + cross-project sharing), memory feedback & precise deletion, multi-modal memory (images/charts), tool memory for agent planning, Redis Streams scheduling + DB optimizations, streaming/non-streaming chat, MCP upgrade, and lightweight quick/full deployment. ✨ New Features **Knowledge Base & Memory** • Added knowledge base support for long-term memory from documents and URLs **Feedback & Memory Management** • Added natural language feedback and correction for memories • Added memory deletion API by memory ID • Added MCP support for memory deletion and feedback **Conversation & Retrieval** • Added chat API with memory-aware retrieval • Added memory filtering with custom tags (Cloud & Open Source) **Multimodal & Tool Memory** • Added tool memory for tool usage history • Added image memory support for conversations and documents 📈 Improvements **Data & Infrastructure** • Upgraded database for better stability and performance **Scheduler** • Rebuilt task scheduler with Redis Streams and queue isolation • Added task priority, auto-recovery, and quota-based scheduling **Deployment & Engineering** • Added lightweight deployment with quick and full modes 🐞 Bug Fixes **Memory Scheduling & Updates** • Fixed legacy scheduling API to ensure correct memory isolation • Fixed memory update logging to show new memories correctly • **2025-08-07** · 🎉 **MemOS v1.0.0 (MemCube) Release** First MemCube release with a word-game demo, LongMemEval evaluation, BochaAISearchRetriever integration, NebulaGraph support, improved search capabilities, and the official Playground launch. ✨ New Features **Playground** • Expanded Playground features and algorithm performance. **MemCube Construction** • Added a text game demo based on the MemCube novel. **Extended Evaluation Set** • Added LongMemEval evaluation results and scripts. 📈 Improvements **Plaintext Memory** • Integrated internet search with Bocha. • Added support for Nebula database. • Added contextual understanding for the tree-structured plaintext memory search interface. 🐞 Bug Fixes **KV Cache Concatenation** • Fixed the concat_cache method. **Plaintext Memory** • Fixed Nebula search-related issues. • **2025-07-07** · 🎉 **MemOS v1.0: Stellar (星河) Preview Release** A SOTA Memory OS for LLMs is now open-sourced. • **2025-07-04** · 🎉 **MemOS Paper Release** MemOS: A Memory OS for AI System is available on arXiv. • **2024-07-04** · 🎉 **Memory3 Model Release at WAIC 2024** The Memory3 model, featuring a memory-layered architecture, was unveiled at the 2024 World Artificial Intelligence Conference. 🚀 Quickstart Guide ☁️ 1、Cloud API (Hosted) Get API Key • Sign up on the MemOS dashboard • Go to **API Keys** and copy your key Next Steps • MemOS Cloud Getting Started Connect to MemOS Cloud and enable memory in minutes. • MemOS Cloud Platform Explore the Cloud dashboard, features, and workflows. 🖥️ 2、Self-Hosted (Local/Private) • Get the repository. • Configure and copy to • The , , and others can be applied for through . • Fill in the corresponding configuration in the file. • Start the service. • Launch via Docker ###### T…