Comparison
Ori-Mnemos vs MemOS
Verdict
Pick Ori-Mnemos if ori-Mnemos is a local-first, persistent agentic memory system leveraging SQLite and TypeScript. It incorporates Recursive Memory Harness (RMH) for AI agents; 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.
Markdown twin · Ori-Mnemos alternatives · MemOS alternatives
GraphCanon updated 3d
vs
Trust & integrity
| Signal | Ori-Mnemos | MemOS |
|---|---|---|
| Maintenance | Very active (1d since push) As of 4w · github_public_v1 | Very active (0d since push) As of 3d · github_public_v1 |
| Provenance | Not a fork · Personal account As of 4w · github_public_v1 | Not a fork · Organization account As of 3d · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of 1mo · osv@v1 | No lockfile (source not queried) As of 1mo · osv@v1 |
| deps.dev advisories | Not queried deps.dev@v1 | Not queried deps.dev@v1 |
| OpenSSF Scorecard | Not queried openssf-scorecard@v1 | Not queried openssf-scorecard@v1 |
Tagline
- Ori-Mnemos
- Local-first persistent agentic memory powered by Recursive Memory Harness (RMH).
- MemOS
- Self-evolving memory OS for LLM & AI Agents: ultra-persistent memory, hybrid-retrieval, and cross-task skill reuse
Stars
- Ori-Mnemos
- 314
- MemOS
- 11k
Forks
- Ori-Mnemos
- 28
- MemOS
- 994
Open issues
- Ori-Mnemos
- 0
- MemOS
- 84
Language
- Ori-Mnemos
- TypeScript
- MemOS
- TypeScript
Adopt for
- Ori-Mnemos
- Ori-Mnemos is a local-first, persistent agentic memory system leveraging SQLite and TypeScript. It incorporates Recursive Memory Harness (RMH) for AI agents.
- MemOS
- 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
- Ori-Mnemos
- -
- MemOS
- -
Runtime
- Ori-Mnemos
- -
- MemOS
- -
License
- Ori-Mnemos
- Apache-2.0
- MemOS
- MemOS is available under the Apache-2.0 license, allowing you to use it freely with certain conditions.
Last pushed
- Ori-Mnemos
- Jul 22, 2026
- MemOS
- Aug 18, 2026
Categories
- Ori-Mnemos
- AI Agents, Data & Retrieval
- MemOS
- AI Agents, Data & Retrieval
Trust and health
Days since push
- Ori-Mnemos
- 1d
- MemOS
- 0d
Open issues (now)
- Ori-Mnemos
- 0
- MemOS
- 84
Stars delta
- Ori-Mnemos
- Unknown
- MemOS
- +497 (30d)
Open issues delta
- Ori-Mnemos
- Unknown
- MemOS
- +4 (30d)
Owner type
- Ori-Mnemos
- User
- MemOS
- Organization
Full report
- Ori-Mnemos
- Trust report
- MemOS
- Trust report
Shared compatibility
- Node.js · Ori-Mnemos: Node.js runtime · MemOS: Node.js runtime
Choose Ori-Mnemos if…
- Tags unique to Ori-Mnemos: agent-memory, ai-agents, knowledge-graph, local-first.
- Ori-Mnemos ships an MCP server manifest.
- When you need a robust, local-first solution that prioritizes offline capabilities and security.
When NOT to use Ori-Mnemos
- When real-time synchronization across devices or cloud integration is a non-negotiable requirement for your application.
- If you are looking for a memory system that leverages distributed databases for scalable access patterns; Ori-Mnemos focuses on local storage using SQLite.
- In environments where complex, multi-node architectures and high availability requirements demand more than a single point of data persistence.
Choose MemOS if…
- 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, long-term-memory, memory-management.
- 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 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.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (aayoawoyemi/Ori-Mnemos) · observed Jul 24, 2026
- GitHub forks (aayoawoyemi/Ori-Mnemos) · observed Jul 24, 2026
- Last push (aayoawoyemi/Ori-Mnemos) · observed Jul 22, 2026
- License file (Apache-2.0) · observed Jul 24, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (MemTensor/MemOS) · observed Aug 18, 2026
- GitHub forks (MemTensor/MemOS) · observed Aug 18, 2026
- Last push (MemTensor/MemOS) · observed Aug 18, 2026
- License file (Apache-2.0) · observed Aug 18, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: Ori-Mnemos 314 · MemOS 11k (synced Jul 24, 2026).
Common questions
- What is the difference between Ori-Mnemos and MemOS?
- Ori-Mnemos: Local-first persistent agentic memory powered by Recursive Memory Harness (RMH).. 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 Ori-Mnemos over MemOS?
- Choose Ori-Mnemos over MemOS when Tags unique to Ori-Mnemos: agent-memory, ai-agents, knowledge-graph, local-first; Ori-Mnemos ships an MCP server manifest; When you need a robust, local-first solution that prioritizes offline capabilities and security.
- When should I choose MemOS over Ori-Mnemos?
- Choose MemOS over Ori-Mnemos when 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, long-term-memory, memory-management; 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 Ori-Mnemos?
- When real-time synchronization across devices or cloud integration is a non-negotiable requirement for your application. If you are looking for a memory system that leverages distributed databases for scalable access patterns; Ori-Mnemos focuses on local storage using SQLite. In environments where complex, multi-node architectures and high availability requirements demand more than a single point of data persistence.
- 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 Ori-Mnemos or MemOS more popular on GitHub?
- MemOS has more GitHub stars (10,758 vs 314). Stars measure visibility, not whether either tool fits your constraints.
- Are Ori-Mnemos and MemOS open source?
- Yes - both are open-source projects on GitHub (Ori-Mnemos: Apache-2.0, MemOS: Apache-2.0).
- Where can I find alternatives to Ori-Mnemos or MemOS?
- GraphCanon lists graph-backed alternatives at Ori-Mnemos alternatives and MemOS alternatives (Ori-Mnemos markdown twin, MemOS markdown twin), 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 mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.
- Which is better maintained, Ori-Mnemos or MemOS?
- Ori-Mnemos: 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 Ori-Mnemos and MemOS?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: Ori-Mnemos trust report; MemOS trust report.