Comparison
Ori-Mnemos vs EverOS
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 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.
Markdown twin · Ori-Mnemos alternatives · EverOS alternatives
GraphCanon updated today
vs
Trust & integrity
| Signal | Ori-Mnemos | EverOS |
|---|---|---|
| Maintenance | Very active (1d since push) As of 3w · github_public_v1 | Very active (1d since push) As of today · github_public_v1 |
| Provenance | Not a fork · Personal account As of 3w · github_public_v1 | Not a fork · Organization account As of today · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of 1mo · osv@v1 | No lockfile (source not queried) As of 2w · 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).
- EverOS
- One portable memory layer for every AI agent
Stars
- Ori-Mnemos
- 314
- EverOS
- 12k
Forks
- Ori-Mnemos
- 28
- EverOS
- 891
Open issues
- Ori-Mnemos
- 0
- EverOS
- 72
Language
- Ori-Mnemos
- TypeScript
- EverOS
- Python
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.
- EverOS
- EverOS is designed as a portable and user-owned memory management solution that supports Markdown format, facilitating easy cross-app memory transfer and evolution.
Persona
- Ori-Mnemos
- -
- EverOS
- -
Runtime
- Ori-Mnemos
- -
- EverOS
- -
License
- Ori-Mnemos
- Apache-2.0
- EverOS
- Apache-2.0
Last pushed
- Ori-Mnemos
- Jul 22, 2026
- EverOS
- Aug 17, 2026
Categories
- Ori-Mnemos
- AI Agents, Data & Retrieval
- EverOS
- AI Agents, Data & Retrieval
Trust and health
Open issues (now)
- Ori-Mnemos
- 0
- EverOS
- 72
Stars delta
- Ori-Mnemos
- Unknown
- EverOS
- +849 (30d)
Open issues delta
- Ori-Mnemos
- Unknown
- EverOS
- +16 (30d)
Owner type
- Ori-Mnemos
- User
- EverOS
- Organization
Full report
- Ori-Mnemos
- Trust report
- EverOS
- Trust report
Shared compatibility
- Python · Ori-Mnemos: Python runtime · EverOS: Python runtime
Choose Ori-Mnemos if…
- Ori-Mnemos is primarily TypeScript; EverOS is Python.
- Tags unique to Ori-Mnemos: ai-agents, knowledge-graph, llm, markdown.
- 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 EverOS if…
- EverOS is primarily Python; Ori-Mnemos is TypeScript.
- Tags unique to EverOS: long-term-memory, markdown-native, memory-management, python3.
- When you require a user-owned memory layer that allows for seamless cross-app integration and evolution using Markdown notes.
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.
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 (EverMind-AI/EverOS) · observed Aug 18, 2026
- GitHub forks (EverMind-AI/EverOS) · observed Aug 18, 2026
- Last push (EverMind-AI/EverOS) · observed Aug 17, 2026
- License file (Apache-2.0) · observed Aug 18, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Aug 2, 2026
GitHub stars on cards: Ori-Mnemos 314 · EverOS 12k (synced Jul 24, 2026).
Common questions
- What is the difference between Ori-Mnemos and EverOS?
- Ori-Mnemos: Local-first persistent agentic memory powered by Recursive Memory Harness (RMH).. EverOS: One portable memory layer for every AI agent. See the comparison table for live GitHub stats and shared categories.
- When should I choose Ori-Mnemos over EverOS?
- Choose Ori-Mnemos over EverOS when Ori-Mnemos is primarily TypeScript; EverOS is Python; Tags unique to Ori-Mnemos: ai-agents, knowledge-graph, llm, markdown; 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 EverOS over Ori-Mnemos?
- Choose EverOS over Ori-Mnemos when EverOS is primarily Python; Ori-Mnemos is TypeScript; Tags unique to EverOS: long-term-memory, markdown-native, memory-management, python3; When you require a user-owned memory layer that allows for seamless cross-app integration and evolution using Markdown notes.
- 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 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.
- Is Ori-Mnemos or EverOS more popular on GitHub?
- EverOS has more GitHub stars (12,114 vs 314). Stars measure visibility, not whether either tool fits your constraints.
- Are Ori-Mnemos and EverOS open source?
- Yes - both are open-source projects on GitHub (Ori-Mnemos: Apache-2.0, EverOS: Apache-2.0).
- Where can I find alternatives to Ori-Mnemos or EverOS?
- GraphCanon lists graph-backed alternatives at Ori-Mnemos alternatives and EverOS alternatives (Ori-Mnemos markdown twin, EverOS 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 EverOS?
- Ori-Mnemos: Very active. EverOS: 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 EverOS?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: Ori-Mnemos trust report; EverOS trust report.