MemoryOS

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MemoryOS is an AI Agents & Automation tool that provides a memory operating system for personalized AI agents. It enables more coherent, personalized, and context-aware interactions through a hierarchical storage architecture.

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At a glance

Pricing

Open Source

Free tier

Yes

API

Yes

Skill level

Technical

About

What is MemoryOS?

MemoryOS is designed to provide a robust memory operating system for personalized AI agents, drawing inspiration from memory management principles in traditional operating systems. It features a hierarchical storage architecture with four core modules: Storage, Updating, Retrieval, and Generation, ensuring comprehensive and efficient memory management. The tool boasts top performance in memory management, achieving significant improvements on long-term memory benchmarks. It offers a plug-and-play architecture for seamless integration of memory modules, including storage engines, update strategies, and retrieval algorithms. MemoryOS also supports universal LLM integration, working with a wide range of models like OpenAI, Deepseek, and Qwen, and provides an Agent Workflow Creation tool (MemoryOS-MCP) to inject long-term memory capabilities into various AI applications.

Best used for

Ideal for developers and data scientists who need to build more coherent, personalized, and context-aware AI agents, manage long-term memory efficiently, and integrate memory capabilities into various AI applications. Especially valuable for achieving state-of-the-art results in long-term memory benchmarks.

Common actions

manage AI agent memory

enhance AI agent personalization

integrate long-term memory

improve context awareness

develop AI agents

face swappinggithub copilotcollaborationopen-sourceworkflowslow-code/no-codeautomated workflowdeepfake"AI Agents"

Capabilities

Key features

Hierarchical memory architecture
Plug-and-play memory modules
Universal LLM support
Agent workflow creation
Top memory performance
Docker integration
Parallelization optimizations

Target Audience

developerdata scientist

Integrations

openaideepseekqwenchromadb

Pricing & Plans

Open Source

Free

FAQs

What is the core architecture of MemoryOS?

MemoryOS adopts a hierarchical storage architecture with four core modules: Storage, Updating, Retrieval, and Generation. This design is inspired by operating system memory management principles to ensure comprehensive and efficient memory handling for AI agents.

Which Large Language Models (LLMs) does MemoryOS support?

MemoryOS is designed for universal LLM support and seamlessly integrates with a wide range of models. This includes popular LLMs such as OpenAI (GPT-4, GPT-3.5), Anthropic (Claude series), Deepseek-R1, and Qwen/Qwen3.

How can I integrate MemoryOS into my AI applications?

MemoryOS offers a plug-and-play memory management architecture, allowing seamless integration of various memory modules. Additionally, the MemoryOS-MCP (MemoryOS Multi-Client Protocol) enables injecting long-term memory capabilities into diverse AI applications by calling modular tools provided by the MCP Server.

Is MemoryOS open-source and how can I get started?

Yes, MemoryOS is an open-source project available on GitHub. You can get started by installing it via pip from PyPI, cloning the GitHub repository, or using Docker images for quick setup and deployment.

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