MemoryOS

At a glance

• Editor score
  4.9 / 10
• Pricing
  Open source
• Best for
  Self-hosters wanting hierarchical conversation memory
• Paid from
  None
• Semantic memory
  Yes
• Facts checked
  13 Oct 2026

• Where it wins

  • Hierarchical short-, mid-, and long-term memory layers
  • Semantic retrieval with automatic profile and knowledge updates
  • MCP tools, Docker deployment, and broad model-client integrations

• Where it doesn't

  • Self-hosted deployment requires your own infrastructure
  • Python is the only listed SDK language
  • Support is limited to community and documentation channels

Our verdict on MemoryOS

MemoryOS is an open-source memory operating system for AI agents that organizes interactions across short-, mid-, and long-term layers. It is aimed at developers and teams that want to run their own memory service for personalized conversations, user profiles, and retained knowledge. The project provides a Python package, an MCP server, a ChromaDB variant, Docker deployment, and a local playground. Its self-hosted model suits solo builders through enterprise teams that can manage deployment directly.

The standout capability is its layered memory design. Pluggable storage, update, and retrieval modules let an implementation separate how memories are saved, revised, and recalled. The add_memory flow ingests conversation history, while semantic retrieval surfaces relevant historical conversations and knowledge. Automatic user-profile and knowledge updating extends the system beyond simple transcript storage. MCP server tools connect agent clients, and listed integrations cover Claude Desktop, Cline, Cursor, OpenAI, Anthropic, Deepseek, Qwen, vLLM, and Llama Factory.

Deployment is the main trade-off. MemoryOS is self-hosted only, with Docker and build-based deployment options rather than a hosted service. Configuration is exposed through the Python package, including memory capacities and retrieval thresholds, so teams should expect to handle infrastructure and tuning themselves. Support is provided through community and documentation channels. Choose MemoryOS when hierarchical semantic memory, profile updates, and MCP access matter and you can operate the stack; choose a hosted memory product instead if managed deployment is a priority.

Your product? Our editors can test MemoryOS in depth and publish a review, labelled as paid · from $99/mo →

MemoryOS pricing

MemoryOS fact sheet

MemoryOS integrations

MemoryOS lists 9 integrations on its own site.

• Claude Desktop
• Cline
• Cursor
• OpenAI
• Anthropic
• Deepseek
• Qwen
• vLLM
• Llama Factory

Alternatives to MemoryOS

• CACloudflare Agent MemoryA cloud API for scoped, searchable memory across AI agent profiles and conversations.9.2
• MMem0A flexible memory layer with semantic, graph, and self-hosted deployment options.8.8
• MMMCP Memory ServiceA broad open-source memory layer for teams that can manage deployment and configuration.7.9

See all MemoryOS alternatives →

Featured on iTechGuides

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Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026

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Last updated 20 Oct 2026 · How we research and update