Comparison
Ori-Mnemos vs honcho
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 honcho if memory Library for Stateful Agents.
Markdown twin · Ori-Mnemos alternatives · honcho alternatives
GraphCanon updated 2d
vs
Trust & integrity
| Signal | Ori-Mnemos | honcho |
|---|---|---|
| Maintenance | Active (23d since push) As of 2d · github_public_v1 | Very active (0d since push) As of 1w · github_public_v1 |
| Provenance | Not a fork · Personal account As of 2d · github_public_v1 | Not a fork · Organization account As of 1w · 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).
- honcho
- Memory library for building stateful agents
Stars
- Ori-Mnemos
- 319
- honcho
- 6.7k
Forks
- Ori-Mnemos
- 27
- honcho
- 824
Open issues
- Ori-Mnemos
- 1
- honcho
- 163
Language
- Ori-Mnemos
- TypeScript
- honcho
- 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.
- honcho
- Memory Library for Stateful Agents
Persona
- Ori-Mnemos
- -
- honcho
- -
Runtime
- Ori-Mnemos
- -
- honcho
- -
License
- Ori-Mnemos
- Apache-2.0
- honcho
- AGPL-3.0
Last pushed
- Ori-Mnemos
- Jul 30, 2026
- honcho
- Aug 18, 2026
Categories
- Ori-Mnemos
- AI Agents, Data & Retrieval
- honcho
- AI Agents, Data & Retrieval
Trust and health
Maintenance
- Ori-Mnemos
- Active (82%)
- honcho
- Very active (96%)
Days since push
- Ori-Mnemos
- 23d
- honcho
- 0d
Open issues (now)
- Ori-Mnemos
- 1
- honcho
- 163
Stars delta
- Ori-Mnemos
- +5 (30d)
- honcho
- +659 (30d)
Open issues delta
- Ori-Mnemos
- +1 (30d)
- honcho
- -3 (30d)
Owner type
- Ori-Mnemos
- User
- honcho
- Organization
Full report
- Ori-Mnemos
- Trust report
- honcho
- Trust report
Shared compatibility
- Python · Ori-Mnemos: Python runtime · honcho: Python runtime
Choose Ori-Mnemos if…
- Ori-Mnemos is primarily TypeScript; honcho is Python.
- License: Ori-Mnemos is Apache-2.0, honcho is AGPL-3.0.
- Tags unique to Ori-Mnemos: knowledge-graph, llm, local-first, 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 honcho if…
- honcho is primarily Python; Ori-Mnemos is TypeScript.
- License: honcho is AGPL-3.0, Ori-Mnemos is Apache-2.0.
- Tags unique to honcho: embeddings, langchain, long-term-memory, memory.
- honcho ships Docker support for self-hosted deployment.
- Requires managing long-term and contextual memory in AI agents for statefulness.
When NOT to use honcho
- Do not need complex SDK support or a customizable framework approach.
- Not interested in using stateful capabilities leveraging multiple APIs such as Gemini, Anthropic, and OpenAI.
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 Aug 23, 2026
- GitHub forks (aayoawoyemi/Ori-Mnemos) · observed Aug 23, 2026
- Last push (aayoawoyemi/Ori-Mnemos) · observed Jul 30, 2026
- License file (Apache-2.0) · observed Aug 23, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (plastic-labs/honcho) · observed Aug 18, 2026
- GitHub forks (plastic-labs/honcho) · observed Aug 18, 2026
- Last push (plastic-labs/honcho) · observed Aug 18, 2026
- License file (AGPL-3.0) · observed Aug 18, 2026
- Decision facts (enrichment) · observed Jul 12, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: Ori-Mnemos 319 · honcho 6.7k (synced Aug 23, 2026).
Common questions
- What is the difference between Ori-Mnemos and honcho?
- Ori-Mnemos: Local-first persistent agentic memory powered by Recursive Memory Harness (RMH).. honcho: Memory library for building stateful agents. See the comparison table for live GitHub stats and shared categories.
- When should I choose Ori-Mnemos over honcho?
- Choose Ori-Mnemos over honcho when Ori-Mnemos is primarily TypeScript; honcho is Python; License: Ori-Mnemos is Apache-2.0, honcho is AGPL-3.0; Tags unique to Ori-Mnemos: knowledge-graph, llm, local-first, 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 honcho over Ori-Mnemos?
- Choose honcho over Ori-Mnemos when honcho is primarily Python; Ori-Mnemos is TypeScript; License: honcho is AGPL-3.0, Ori-Mnemos is Apache-2.0; Tags unique to honcho: embeddings, langchain, long-term-memory, memory; honcho ships Docker support for self-hosted deployment; Requires managing long-term and contextual memory in AI agents for statefulness.
- 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 honcho?
- Do not need complex SDK support or a customizable framework approach. Not interested in using stateful capabilities leveraging multiple APIs such as Gemini, Anthropic, and OpenAI.
- Is Ori-Mnemos or honcho more popular on GitHub?
- honcho has more GitHub stars (6,703 vs 319). Stars measure visibility, not whether either tool fits your constraints.
- Are Ori-Mnemos and honcho open source?
- Yes - both are open-source projects on GitHub (Ori-Mnemos: Apache-2.0, honcho: AGPL-3.0).
- Where can I find alternatives to Ori-Mnemos or honcho?
- GraphCanon lists graph-backed alternatives at Ori-Mnemos alternatives and honcho alternatives (Ori-Mnemos markdown twin, honcho 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 honcho?
- Ori-Mnemos: Active. honcho: 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 honcho?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: Ori-Mnemos trust report; honcho trust report.