--- title: "openakita vs agents-from-scratch" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/openakita-openakita-vs-pguso-agents-from-scratch" tools: ["openakita-openakita", "pguso-agents-from-scratch"] --- # openakita vs agents-from-scratch *GraphCanon updated Sep 20, 2026* ## Verdict Pick openakita if decision-relevant data on OpenAkita; pick agents-from-scratch if agents-from-scratch is for those who want absolute control over their AI agent development using only local resources and Python, focusing on deep learning without relying on external frameworks or cloud dependencies. [openakita](http://openakita.ai) reports 2.0k GitHub stars, 277 forks, and 42 open issues, last pushed Sep 18, 2026. [agents-from-scratch](https://github.com/pguso/agents-from-scratch) has 1.0k stars, 251 forks, and 4 open issues, last pushed Jul 25, 2026. Figures are from public GitHub metadata via [openakita's repository](https://github.com/openakita/openakita) and [agents-from-scratch's repository](https://github.com/pguso/agents-from-scratch). | | [openakita](/tools/openakita-openakita.md) | [agents-from-scratch](/tools/pguso-agents-from-scratch.md) | | --- | --- | --- | | Tagline | An open-source AI assistant framework with skills and agent architecture | Build AI agents locally without relying on frameworks or cloud APIs. | | Stars | 1,986 | 1,017 | | Forks | 277 | 251 | | Open issues | 42 | 4 | | Language | Python | Python | | Adopt for | Decision-relevant data on OpenAkita | agents-from-scratch is for those who want absolute control over their AI agent development using only local resources and Python, focusing on deep learning without relying on external frameworks or cloud dependencies. | | Persona | - | - | | Runtime | - | - | | License | AGPL-3.0 | MIT License: Permissive licensing allowing free use and distribution for both commercial and non-commercial purposes. | | Categories | AI Agents | AI Agents, Developer Tools | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [openakita](/tools/openakita-openakita.md) | [agents-from-scratch](/tools/pguso-agents-from-scratch.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Steady (60%) | | Days since push | 1d | 56d | | Open issues (now) | 42 | 4 | | Stars delta | +31 (30d) | +63 (30d) | | Full report | [trust report](/tools/openakita-openakita/trust.md) | [trust report](/tools/pguso-agents-from-scratch/trust.md) | ## Shared compatibility - **Python**: [openakita](/tools/openakita-openakita.md) - Python runtime; [agents-from-scratch](/tools/pguso-agents-from-scratch.md) - Python runtime ## Decision facts: openakita - **Adopt for:** Decision-relevant data on OpenAkita ## Decision facts: agents-from-scratch - **Requirements:** Min 8 GB RAM; Local large language model availability is critical as the tool does not utilize any cloud APIs. - **Adopt for:** agents-from-scratch is for those who want absolute control over their AI agent development using only local resources and Python, focusing on deep learning without relying on external frameworks or cloud dependencies. - **License detail:** MIT License: Permissive licensing allowing free use and distribution for both commercial and non-commercial purposes. ## Choose when ### Choose openakita if… - License: openakita is AGPL-3.0, agents-from-scratch is MIT. - Tags unique to openakita: agent, ai, assistant, automation. - openakita ships Docker support for self-hosted deployment. - For developing agents that can be customized with specific modular skills suitable for diverse assistant tasks ### Choose agents-from-scratch if… - License: agents-from-scratch is MIT, openakita is AGPL-3.0. - Requirements: Min 8 GB RAM; Local large language model availability is critical as the tool does not utilize any cloud APIs.. - Tags unique to agents-from-scratch: agent-architecture, ai-agents, llm, local-llm. - Also covers Developer Tools. - You plan to teach yourself or others about the fundamentals of creating AI agents from ground zero with complete transparency into each layer of architecture. ## When NOT to use openakita - Avoid if proprietary or non-open source solutions are preferred as OpenAkita's AGPL-3.0 license mandates sharing modifications publicly - Consider alternatives if a less modular approach is desired, since OpenAkita strongly emphasizes a skills-based agent architecture which may complicate straightforward integrations ## When NOT to use agents-from-scratch - You are working on an application that needs to be deployed quickly. The tool's approach from first principles can be time-consuming compared to using established frameworks. - If you need scalability or cloud capabilities such as easy scaling with demand, this tool will not provide these features since it strictly operates on local infrastructure. ## Common questions ### What is the difference between openakita and agents-from-scratch? openakita: An open-source AI assistant framework with skills and agent architecture. agents-from-scratch: Build AI agents locally without relying on frameworks or cloud APIs.. See the comparison table for live GitHub stats and shared categories. ### When should I choose openakita over agents-from-scratch? Choose openakita over agents-from-scratch when License: openakita is AGPL-3.0, agents-from-scratch is MIT; Tags unique to openakita: agent, ai, assistant, automation; openakita ships Docker support for self-hosted deployment; For developing agents that can be customized with specific modular skills suitable for diverse assistant tasks. ### When should I choose agents-from-scratch over openakita? Choose agents-from-scratch over openakita when License: agents-from-scratch is MIT, openakita is AGPL-3.0; Requirements: Min 8 GB RAM; Local large language model availability is critical as the tool does not utilize any cloud APIs.; Tags unique to agents-from-scratch: agent-architecture, ai-agents, llm, local-llm; Also covers Developer Tools; You plan to teach yourself or others about the fundamentals of creating AI agents from ground zero with complete transparency into each layer of architecture. ### When should I avoid openakita? Avoid if proprietary or non-open source solutions are preferred as OpenAkita's AGPL-3.0 license mandates sharing modifications publicly Consider alternatives if a less modular approach is desired, since OpenAkita strongly emphasizes a skills-based agent architecture which may complicate straightforward integrations ### When should I avoid agents-from-scratch? You are working on an application that needs to be deployed quickly. The tool's approach from first principles can be time-consuming compared to using established frameworks. If you need scalability or cloud capabilities such as easy scaling with demand, this tool will not provide these features since it strictly operates on local infrastructure. ### Is openakita or agents-from-scratch more popular on GitHub? openakita has more GitHub stars (1,986 vs 1,017). Stars measure visibility, not whether either tool fits your constraints. ### Are openakita and agents-from-scratch open source? Yes - both are open-source projects on GitHub (openakita: AGPL-3.0, agents-from-scratch: MIT). ### Where can I find alternatives to openakita or agents-from-scratch? GraphCanon lists graph-backed alternatives at [openakita alternatives](/tools/openakita-openakita/alternatives) and [agents-from-scratch alternatives](/tools/pguso-agents-from-scratch/alternatives) ([openakita markdown twin](/tools/openakita-openakita/alternatives.md), [agents-from-scratch markdown twin](/tools/pguso-agents-from-scratch/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/openakita-openakita-vs-pguso-agents-from-scratch.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, openakita or agents-from-scratch? openakita: Very active. agents-from-scratch: Steady. 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 openakita and agents-from-scratch? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [openakita trust report](/tools/openakita-openakita/trust); [agents-from-scratch trust report](/tools/pguso-agents-from-scratch/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=openakita-openakita`](/api/graphcanon/graph?tool=openakita-openakita) - 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/_