--- title: "EverOS vs MemOS" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/evermind-ai-everos-vs-memtensor-memos" tools: ["evermind-ai-everos", "memtensor-memos"] --- # EverOS vs MemOS *GraphCanon updated Aug 18, 2026* ## Verdict Pick EverOS if everOS is designed as a portable and user-owned memory management solution that supports Markdown format, facilitating easy cross-app memory transfer and evolution; pick MemOS if memOS is a self-evolving operating system tailored for LSTM systems and AI agents, offering ultra-persistent memory, hybrid retrieval technologies, and skill reuse across tasks. [EverOS](https://evermind.ai/everos) reports 12k GitHub stars, 891 forks, and 72 open issues, last pushed Aug 17, 2026. [MemOS](https://memos.openmem.net) has 11k stars, 994 forks, and 84 open issues, last pushed Aug 18, 2026. Figures are from public GitHub metadata via [EverOS's repository](https://github.com/EverMind-AI/EverOS) and [MemOS's repository](https://github.com/MemTensor/MemOS). | | [EverOS](/tools/evermind-ai-everos.md) | [MemOS](/tools/memtensor-memos.md) | | --- | --- | --- | | Tagline | One portable memory layer for every AI agent | Self-evolving memory OS for LLM & AI Agents: ultra-persistent memory, hybrid-retrieval, and cross-task skill reuse | | Stars | 12,114 | 10,758 | | Forks | 891 | 994 | | Open issues | 72 | 84 | | Language | Python | TypeScript | | Adopt for | EverOS is designed as a portable and user-owned memory management solution that supports Markdown format, facilitating easy cross-app memory transfer and evolution. | MemOS is a self-evolving operating system tailored for LSTM systems and AI agents, offering ultra-persistent memory, hybrid retrieval technologies, and skill reuse across tasks. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | MemOS is available under the Apache-2.0 license, allowing you to use it freely with certain conditions. | | Categories | AI Agents, Data & Retrieval | AI Agents, Data & Retrieval | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [EverOS](/tools/evermind-ai-everos.md) | [MemOS](/tools/memtensor-memos.md) | | --- | --- | --- | | Days since push | 1d | 0d | | Open issues (now) | 72 | 84 | | Stars delta | +849 (30d) | +497 (30d) | | Open issues delta | +16 (30d) | +4 (30d) | | Full report | [trust report](/tools/evermind-ai-everos/trust.md) | [trust report](/tools/memtensor-memos/trust.md) | ## Decision facts: EverOS - **Adopt for:** EverOS is designed as a portable and user-owned memory management solution that supports Markdown format, facilitating easy cross-app memory transfer and evolution. ## Decision facts: MemOS - **Pricing:** unknown - Pricing details are not clearly specified in the repository data, but the self-hosted option provides flexibility at the expense of managing infrastructure costs. - **Requirements:** Requires Docker; Self-hosting MemOS typically requires setting up Neo4j and Qdrant. The cloud API or OpenClaw Cloud Plugin options do not require these components. - **Adopt for:** MemOS is a self-evolving operating system tailored for LSTM systems and AI agents, offering ultra-persistent memory, hybrid retrieval technologies, and skill reuse across tasks. - **License detail:** MemOS is available under the Apache-2.0 license, allowing you to use it freely with certain conditions. ## Choose when ### Choose EverOS if… - EverOS is primarily Python; MemOS is TypeScript. - Tags unique to EverOS: agent-memory, local-first, markdown-native, python3. - When you require a user-owned memory layer that allows for seamless cross-app integration and evolution using Markdown notes. ### Choose MemOS if… - MemOS is primarily TypeScript; EverOS is Python. - Pricing: Pricing details are not clearly specified in the repository data, but the self-hosted option provides flexibility at the expense of managing infrastructure costs.. - Requirements: Requires Docker; Self-hosting MemOS typically requires setting up Neo4j and Qdrant. The cloud API or OpenClaw Cloud Plugin options do not require these components.. - Tags unique to MemOS: agent, agentic-ai, llm. - MemOS ships Docker support for self-hosted deployment. - If you require ultra-persistent memory management within your application for long-term storage. ## When NOT to use EverOS - If your project requires a non-markdown-based memory layer, since EverOS is specifically designed for Markdown-format memories and may not integrate well with other formats. - When the requirement is strictly cloud-centric without local-first capabilities; EverOS focuses on being local-first before operating across applications. ## When NOT to use MemOS - If you prefer fully managed solutions and have no preference over where your data is stored (hosted in MemOS Cloud). - When minimal setup overhead is a critical requirement since self-hosting MemOS necessitates Neo4j and Qdrant for optimal performance. - In scenarios preferring simpler on-device solutions as MemOS could be more complex to set up compared to other lightweight plugins or services. ## Common questions ### What is the difference between EverOS and MemOS? EverOS: One portable memory layer for every AI agent. MemOS: Self-evolving memory OS for LLM & AI Agents: ultra-persistent memory, hybrid-retrieval, and cross-task skill reuse. See the comparison table for live GitHub stats and shared categories. ### When should I choose EverOS over MemOS? Choose EverOS over MemOS when EverOS is primarily Python; MemOS is TypeScript; Tags unique to EverOS: agent-memory, local-first, markdown-native, python3; When you require a user-owned memory layer that allows for seamless cross-app integration and evolution using Markdown notes. ### When should I choose MemOS over EverOS? Choose MemOS over EverOS when MemOS is primarily TypeScript; EverOS is Python; Pricing: Pricing details are not clearly specified in the repository data, but the self-hosted option provides flexibility at the expense of managing infrastructure costs.; Requirements: Requires Docker; Self-hosting MemOS typically requires setting up Neo4j and Qdrant. The cloud API or OpenClaw Cloud Plugin options do not require these components.; Tags unique to MemOS: agent, agentic-ai, llm; MemOS ships Docker support for self-hosted deployment; If you require ultra-persistent memory management within your application for long-term storage. ### When should I avoid EverOS? If your project requires a non-markdown-based memory layer, since EverOS is specifically designed for Markdown-format memories and may not integrate well with other formats. When the requirement is strictly cloud-centric without local-first capabilities; EverOS focuses on being local-first before operating across applications. ### When should I avoid MemOS? If you prefer fully managed solutions and have no preference over where your data is stored (hosted in MemOS Cloud). When minimal setup overhead is a critical requirement since self-hosting MemOS necessitates Neo4j and Qdrant for optimal performance. In scenarios preferring simpler on-device solutions as MemOS could be more complex to set up compared to other lightweight plugins or services. ### Is EverOS or MemOS more popular on GitHub? EverOS has more GitHub stars (12,114 vs 10,758). Stars measure visibility, not whether either tool fits your constraints. ### Are EverOS and MemOS open source? Yes - both are open-source projects on GitHub (EverOS: Apache-2.0, MemOS: Apache-2.0). ### Where can I find alternatives to EverOS or MemOS? GraphCanon lists graph-backed alternatives at [EverOS alternatives](/tools/evermind-ai-everos/alternatives) and [MemOS alternatives](/tools/memtensor-memos/alternatives) ([EverOS markdown twin](/tools/evermind-ai-everos/alternatives.md), [MemOS markdown twin](/tools/memtensor-memos/alternatives.md)), ranked by typed relationship edges rather than popularity votes. ### Is there a machine-readable version of this comparison? Yes. The markdown twin at [this comparison](/compare/evermind-ai-everos-vs-memtensor-memos.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, EverOS or MemOS? EverOS: Very active. MemOS: Very active. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance. ### Where are the full trust reports for EverOS and MemOS? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [EverOS trust report](/tools/evermind-ai-everos/trust); [MemOS trust report](/tools/memtensor-memos/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=evermind-ai-everos`](/api/graphcanon/graph?tool=evermind-ai-everos) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_