--- title: "Ori-Mnemos vs agentic-rag-for-dummies" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/aayoawoyemi-ori-mnemos-vs-giovannipasq-agentic-rag-for-dummies" tools: ["aayoawoyemi-ori-mnemos", "giovannipasq-agentic-rag-for-dummies"] --- # Ori-Mnemos vs agentic-rag-for-dummies *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 agentic-rag-for-dummies if agentic RAG for Dummies simplifies the setup of retrieval-augmented generation agents using LangGraph and Ollama models. [Ori-Mnemos](https://orimnemos.com.) reports 319 GitHub stars, 27 forks, and 1 open issues, last pushed Jul 30, 2026. [agentic-rag-for-dummies](https://github.com/GiovanniPasq/agentic-rag-for-dummies) has 3.9k stars, 499 forks, and 0 open issues, last pushed Jul 25, 2026. Figures are from public GitHub metadata via [Ori-Mnemos's repository](https://github.com/aayoawoyemi/Ori-Mnemos) and [agentic-rag-for-dummies's repository](https://github.com/GiovanniPasq/agentic-rag-for-dummies). | | [Ori-Mnemos](/tools/aayoawoyemi-ori-mnemos.md) | [agentic-rag-for-dummies](/tools/giovannipasq-agentic-rag-for-dummies.md) | | --- | --- | --- | | Tagline | Local-first persistent agentic memory powered by Recursive Memory Harness (RMH). | A modular Agentic RAG built with LangGraph for learning Retrieval-Augmented Generation Agents | | Stars | 319 | 3,893 | | Forks | 27 | 499 | | Open issues | 1 | 0 | | Language | TypeScript | Jupyter Notebook | | 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. | Agentic RAG for Dummies simplifies the setup of retrieval-augmented generation agents using LangGraph and Ollama models. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | MIT | | 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) | [agentic-rag-for-dummies](/tools/giovannipasq-agentic-rag-for-dummies.md) | | --- | --- | --- | | Days since push | 23d | 19d | | Open issues (now) | 1 | 0 | | Stars delta | +5 (30d) | Unknown | | Open issues delta | +1 (30d) | Unknown | | Full report | [trust report](/tools/aayoawoyemi-ori-mnemos/trust.md) | [trust report](/tools/giovannipasq-agentic-rag-for-dummies/trust.md) | ## Shared compatibility - **Python**: [Ori-Mnemos](/tools/aayoawoyemi-ori-mnemos.md) - Python runtime; [agentic-rag-for-dummies](/tools/giovannipasq-agentic-rag-for-dummies.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: agentic-rag-for-dummies - **Adopt for:** Agentic RAG for Dummies simplifies the setup of retrieval-augmented generation agents using LangGraph and Ollama models. ## Choose when ### Choose Ori-Mnemos if… - Ori-Mnemos is primarily TypeScript; agentic-rag-for-dummies is Jupyter Notebook. - License: Ori-Mnemos is Apache-2.0, agentic-rag-for-dummies is MIT. - 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. ### Choose agentic-rag-for-dummies if… - agentic-rag-for-dummies is primarily Jupyter Notebook; Ori-Mnemos is TypeScript. - License: agentic-rag-for-dummies is MIT, Ori-Mnemos is Apache-2.0. - Tags unique to agentic-rag-for-dummies: agent, agentic-ai, bm25, gradio. - When aiming to quickly develop a retrieval-augmented generation agent, thanks to its streamlined setup with LangGraph. ## 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 agentic-rag-for-dummies - If smaller language model sizes are required as they might ignore retrieval instructions or hallucinate details. - Projects sensitive about Docker and system requirements must carefully review the outlined conditions for deployment. ## Common questions ### What is the difference between Ori-Mnemos and agentic-rag-for-dummies? Ori-Mnemos: Local-first persistent agentic memory powered by Recursive Memory Harness (RMH).. agentic-rag-for-dummies: A modular Agentic RAG built with LangGraph for learning Retrieval-Augmented Generation Agents. See the comparison table for live GitHub stats and shared categories. ### When should I choose Ori-Mnemos over agentic-rag-for-dummies? Choose Ori-Mnemos over agentic-rag-for-dummies when Ori-Mnemos is primarily TypeScript; agentic-rag-for-dummies is Jupyter Notebook; License: Ori-Mnemos is Apache-2.0, agentic-rag-for-dummies is MIT; 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 agentic-rag-for-dummies over Ori-Mnemos? Choose agentic-rag-for-dummies over Ori-Mnemos when agentic-rag-for-dummies is primarily Jupyter Notebook; Ori-Mnemos is TypeScript; License: agentic-rag-for-dummies is MIT, Ori-Mnemos is Apache-2.0; Tags unique to agentic-rag-for-dummies: agent, agentic-ai, bm25, gradio; When aiming to quickly develop a retrieval-augmented generation agent, thanks to its streamlined setup with LangGraph. ### 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 agentic-rag-for-dummies? If smaller language model sizes are required as they might ignore retrieval instructions or hallucinate details. Projects sensitive about Docker and system requirements must carefully review the outlined conditions for deployment. ### Is Ori-Mnemos or agentic-rag-for-dummies more popular on GitHub? agentic-rag-for-dummies has more GitHub stars (3,893 vs 319). Stars measure visibility, not whether either tool fits your constraints. ### Are Ori-Mnemos and agentic-rag-for-dummies open source? Yes - both are open-source projects on GitHub (Ori-Mnemos: Apache-2.0, agentic-rag-for-dummies: MIT). ### Where can I find alternatives to Ori-Mnemos or agentic-rag-for-dummies? GraphCanon lists graph-backed alternatives at [Ori-Mnemos alternatives](/tools/aayoawoyemi-ori-mnemos/alternatives) and [agentic-rag-for-dummies alternatives](/tools/giovannipasq-agentic-rag-for-dummies/alternatives) ([Ori-Mnemos markdown twin](/tools/aayoawoyemi-ori-mnemos/alternatives.md), [agentic-rag-for-dummies markdown twin](/tools/giovannipasq-agentic-rag-for-dummies/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-giovannipasq-agentic-rag-for-dummies.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, Ori-Mnemos or agentic-rag-for-dummies? Ori-Mnemos: Active. agentic-rag-for-dummies: 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 agentic-rag-for-dummies? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [Ori-Mnemos trust report](/tools/aayoawoyemi-ori-mnemos/trust); [agentic-rag-for-dummies trust report](/tools/giovannipasq-agentic-rag-for-dummies/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/_