--- title: "Ori-Mnemos vs pmb" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/aayoawoyemi-ori-mnemos-vs-oleksiijko-pmb" tools: ["aayoawoyemi-ori-mnemos", "oleksiijko-pmb"] --- # Ori-Mnemos vs pmb *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 pmb if pmb - Local-first persistent memory for AI coding agents. [Ori-Mnemos](https://orimnemos.com.) reports 319 GitHub stars, 27 forks, and 1 open issues, last pushed Jul 30, 2026. [pmb](https://pypi.org/project/pmb-ai/) has 295 stars, 23 forks, and 9 open issues, last pushed Aug 17, 2026. Figures are from public GitHub metadata via [Ori-Mnemos's repository](https://github.com/aayoawoyemi/Ori-Mnemos) and [pmb's repository](https://github.com/oleksiijko/pmb). | | [Ori-Mnemos](/tools/aayoawoyemi-ori-mnemos.md) | [pmb](/tools/oleksiijko-pmb.md) | | --- | --- | --- | | Tagline | Local-first persistent agentic memory powered by Recursive Memory Harness (RMH). | Local-first persistent memory for AI coding agents with offline and multilingual capabilities. | | Stars | 319 | 295 | | Forks | 27 | 23 | | Open issues | 1 | 9 | | 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. | pmb - Local-first persistent memory for AI coding agents | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | Apache-2.0 | | 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) | [pmb](/tools/oleksiijko-pmb.md) | | --- | --- | --- | | Maintenance | Active (82%) | Very active (96%) | | Days since push | 23d | 6d | | Open issues (now) | 1 | 9 | | Stars delta | +5 (30d) | +16 (30d) | | Open issues delta | +1 (30d) | +4 (30d) | | Full report | [trust report](/tools/aayoawoyemi-ori-mnemos/trust.md) | [trust report](/tools/oleksiijko-pmb/trust.md) | ## 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: pmb - **Requirements:** No explicit requirements listed in repository data, but likely Python and compatible SQL database setup. - **Adopt for:** pmb - Local-first persistent memory for AI coding agents - **License detail:** Apache-2.0 ## Choose when ### Choose Ori-Mnemos if… - Ori-Mnemos is primarily TypeScript; pmb is Python. - Tags unique to Ori-Mnemos: agent-memory, 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 pmb if… - pmb is primarily Python; Ori-Mnemos is TypeScript. - Requirements: No explicit requirements listed in repository data, but likely Python and compatible SQL database setup.. - Tags unique to pmb: ai-memory, bm25, claude-code, codex. - - When you need a solution that integrates directly with popular AI coding agents such as Claude Code, Cursor, and Codex. ## 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 pmb - - In scenarios where real-time data retrieval is essential since pmb focuses on local storage rather than cloud-based synchronization. - - If your project requires heavy reliance on online services or if offline functionality doesn't provide a necessary advantage. - - When the specific use case does not benefit from having multilingual capabilities for AI coding tasks. ## Common questions ### What is the difference between Ori-Mnemos and pmb? Ori-Mnemos: Local-first persistent agentic memory powered by Recursive Memory Harness (RMH).. pmb: Local-first persistent memory for AI coding agents with offline and multilingual capabilities.. See the comparison table for live GitHub stats and shared categories. ### When should I choose Ori-Mnemos over pmb? Choose Ori-Mnemos over pmb when Ori-Mnemos is primarily TypeScript; pmb is Python; Tags unique to Ori-Mnemos: agent-memory, 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 pmb over Ori-Mnemos? Choose pmb over Ori-Mnemos when pmb is primarily Python; Ori-Mnemos is TypeScript; Requirements: No explicit requirements listed in repository data, but likely Python and compatible SQL database setup.; Tags unique to pmb: ai-memory, bm25, claude-code, codex; - When you need a solution that integrates directly with popular AI coding agents such as Claude Code, Cursor, and Codex. ### 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 pmb? - In scenarios where real-time data retrieval is essential since pmb focuses on local storage rather than cloud-based synchronization. - If your project requires heavy reliance on online services or if offline functionality doesn't provide a necessary advantage. - When the specific use case does not benefit from having multilingual capabilities for AI coding tasks. ### Is Ori-Mnemos or pmb more popular on GitHub? Ori-Mnemos has more GitHub stars (319 vs 295). Stars measure visibility, not whether either tool fits your constraints. ### Are Ori-Mnemos and pmb open source? Yes - both are open-source projects on GitHub (Ori-Mnemos: Apache-2.0, pmb: Apache-2.0). ### Where can I find alternatives to Ori-Mnemos or pmb? GraphCanon lists graph-backed alternatives at [Ori-Mnemos alternatives](/tools/aayoawoyemi-ori-mnemos/alternatives) and [pmb alternatives](/tools/oleksiijko-pmb/alternatives) ([Ori-Mnemos markdown twin](/tools/aayoawoyemi-ori-mnemos/alternatives.md), [pmb markdown twin](/tools/oleksiijko-pmb/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-oleksiijko-pmb.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, Ori-Mnemos or pmb? Ori-Mnemos: Active. pmb: 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 pmb? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [Ori-Mnemos trust report](/tools/aayoawoyemi-ori-mnemos/trust); [pmb trust report](/tools/oleksiijko-pmb/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/_