--- title: "Ori-Mnemos vs honcho" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/aayoawoyemi-ori-mnemos-vs-plastic-labs-honcho" tools: ["aayoawoyemi-ori-mnemos", "plastic-labs-honcho"] --- # Ori-Mnemos vs honcho *GraphCanon updated Aug 23, 2026* ## 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. [Ori-Mnemos](https://orimnemos.com.) reports 319 GitHub stars, 27 forks, and 1 open issues, last pushed Jul 30, 2026. [honcho](https://docs.honcho.dev) has 6.7k stars, 824 forks, and 163 open issues, last pushed Aug 18, 2026. Figures are from public GitHub metadata via [Ori-Mnemos's repository](https://github.com/aayoawoyemi/Ori-Mnemos) and [honcho's repository](https://github.com/plastic-labs/honcho). | | [Ori-Mnemos](/tools/aayoawoyemi-ori-mnemos.md) | [honcho](/tools/plastic-labs-honcho.md) | | --- | --- | --- | | Tagline | Local-first persistent agentic memory powered by Recursive Memory Harness (RMH). | Memory library for building stateful agents | | Stars | 319 | 6,703 | | Forks | 27 | 824 | | Open issues | 1 | 163 | | Language | TypeScript | Python | | Adopt for | Ori-Mnemos is a local-first, persistent agentic memory system leveraging SQLite and TypeScript. It incorporates Recursive Memory Harness (RMH) for AI agents. | Memory Library for Stateful Agents | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | AGPL-3.0 | | Categories | AI Agents, Data & Retrieval | AI Agents, Data & Retrieval | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [Ori-Mnemos](/tools/aayoawoyemi-ori-mnemos.md) | [honcho](/tools/plastic-labs-honcho.md) | | --- | --- | --- | | Maintenance | Active (82%) | Very active (96%) | | Days since push | 23d | 0d | | Open issues (now) | 1 | 163 | | Stars delta | +5 (30d) | +659 (30d) | | Open issues delta | +1 (30d) | -3 (30d) | | Owner type | User | Organization | | Full report | [trust report](/tools/aayoawoyemi-ori-mnemos/trust.md) | [trust report](/tools/plastic-labs-honcho/trust.md) | ## Shared compatibility - **Python**: [Ori-Mnemos](/tools/aayoawoyemi-ori-mnemos.md) - Python runtime; [honcho](/tools/plastic-labs-honcho.md) - Python runtime ## Decision facts: Ori-Mnemos - **Adopt for:** Ori-Mnemos is a local-first, persistent agentic memory system leveraging SQLite and TypeScript. It incorporates Recursive Memory Harness (RMH) for AI agents. ## Decision facts: honcho - **Adopt for:** Memory Library for Stateful Agents ## Choose when ### 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. ### 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 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 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. ## 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](/tools/aayoawoyemi-ori-mnemos/alternatives) and [honcho alternatives](/tools/plastic-labs-honcho/alternatives) ([Ori-Mnemos markdown twin](/tools/aayoawoyemi-ori-mnemos/alternatives.md), [honcho markdown twin](/tools/plastic-labs-honcho/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/aayoawoyemi-ori-mnemos-vs-plastic-labs-honcho.md) 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](/tools/aayoawoyemi-ori-mnemos/trust); [honcho trust report](/tools/plastic-labs-honcho/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=aayoawoyemi-ori-mnemos`](/api/graphcanon/graph?tool=aayoawoyemi-ori-mnemos) - 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/_