LibreAI / AI Agents / MemOS
// agents · MemTensor/MemOS

MemOS

Self-evolving memory OS for LLMs and agents: persistent graph memory, hybrid retrieval, skill reuse.

★ 11.8k stars⑂ 1.1k forksApache-2.0updated 2026-10
▦ visual — this project's README ships no embeddable screenshot,
so here's a placeholder. The guide below is complete regardless.
// project facts

Project facts

MemOS is an open-source ai agents project by MemTensor (MemTensor/MemOS on GitHub). It has 11,763 GitHub stars and 1,069 forks, is released under the Apache-2.0 license, and was last updated on GitHub on 8 October 2026.

Repository
MemTensor/MemOS
GitHub stars
11,763
Forks
1,069
License
Apache-2.0
Last updated on GitHub
8 October 2026
Category
AI Agents
Listing
Full install guide
Official site
Official site
// how it works

How it works

  1. Pick your deployment shape

    Choose the hosted Cloud API for zero infrastructure, self-hosting for your own servers, or the local plugin for 100% on-device memory in OpenClaw, Hermes or DeepSeek Harness.

  2. Set it up

    For self-hosting, clone the repo, copy docker/.env.example to .env and fill in your LLM and embedder API keys; for cloud, create an API key in the dashboard.

  3. Start the service

    Bring up MemOS with Docker Compose (API, Neo4j and Qdrant) and confirm it answers on port 8000.

  4. Add and search your first memories

    Create a memory cube, add conversation messages through the API, then search them back and watch recall improve future agent turns.

// features

Why people love it

Unified memory API

One API to add, retrieve, edit and delete memory, structured as an inspectable graph rather than an opaque embedding store.

Multimodal and tool memory

Natively stores text, images, tool traces and personas, retrieved and reasoned over together in one system.

Memory cubes

Manage multiple knowledge bases as composable cubes with isolation and controlled sharing across users, projects and agents.

Asynchronous ingestion

The MemScheduler runs memory operations asynchronously, keeping latency low under high concurrency for production stability.

Feedback and correction

Refine memory with natural-language feedback - correcting, supplementing or replacing memories over time, which underpins its self-evolving behavior.

Plugins for agent frameworks

Official cloud and local plugins for OpenClaw, Hermes Agent and DeepSeek Harness add automatic recall before tasks and capture after them, with a local Memory Viewer.

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// run it

Run it yourself

  1. Clone the repository

    Clone MemOS for self-hosting; cloud and plugin users can skip the clone.

    git clone https://github.com/MemTensor/MemOS.git
    cd MemOS
  2. Configure your keys

    Copy the example environment file and fill in your LLM provider and embedder API keys.

    cp docker/.env.example .env  # fill in your API keys in .env
  3. Start the service

    Launch MemOS with Docker Compose - it starts the API together with Neo4j and Qdrant - then call it on port 8000.

    cd docker
    docker compose up
// use cases

What you can build

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// faq

Questions, answered

Who maintains MemOS?

MemOS is developed by MemTensor and contributors; the research is described in the paper 'MemOS: A Memory OS for AI System' (arXiv 2507.03724).

Is MemOS free?

The open-source code is Apache-2.0 licensed and self-hosting is free. The hosted MemOS Cloud API is a managed service with its own key and terms.

Does it need a paid API key?

Self-hosting needs your own LLM and embedder keys (set in .env) for memory extraction and search; the cloud API uses a MemOS API key instead. The local plugin keeps data on-device.

How does MemOS compare with Mem0 or EverOS?

All three give agents long-term memory; MemOS centers on a graph-structured memory OS with composable memory cubes and an async scheduler, and ships first-party plugins for OpenClaw, Hermes and DeepSeek Harness.

How do I get started?

For the fastest path, get a cloud API key from the MemOS dashboard and call the add/search endpoints; for self-hosting, clone, fill .env, and docker compose up.

// keep exploring

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// alternatives

Alternatives in AI Agents

The most-starred other AI Agents projects in the LibreAI catalogue — the realistic shortlist if MemOS is not the right fit.

Get MemOS

Free and open — grab the source, star the repo, and start creating.