--- title: "agents-from-scratch vs agor" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/pguso-agents-from-scratch-vs-preset-io-agor" tools: ["pguso-agents-from-scratch", "preset-io-agor"] --- # agents-from-scratch vs agor *GraphCanon updated Sep 20, 2026* ## Verdict 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; pick agor if agor is a team-centric development platform built for orchestrating AI agents in coding and collaboration tasks. [agents-from-scratch](https://github.com/pguso/agents-from-scratch) reports 1.0k GitHub stars, 251 forks, and 4 open issues, last pushed Jul 25, 2026. [agor](https://agor.live) has 1.4k stars, 121 forks, and 219 open issues, last pushed Sep 19, 2026. Figures are from public GitHub metadata via [agents-from-scratch's repository](https://github.com/pguso/agents-from-scratch) and [agor's repository](https://github.com/preset-io/agor). | | [agents-from-scratch](/tools/pguso-agents-from-scratch.md) | [agor](/tools/preset-io-agor.md) | | --- | --- | --- | | Tagline | Build AI agents locally without relying on frameworks or cloud APIs. | team command center for all things agentic | | Stars | 1,017 | 1,406 | | Forks | 251 | 121 | | Open issues | 4 | 219 | | Language | Python | TypeScript | | 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. | Agor is a team-centric development platform built for orchestrating AI agents in coding and collaboration tasks. | | Persona | - | - | | Runtime | - | - | | License | MIT License: Permissive licensing allowing free use and distribution for both commercial and non-commercial purposes. | Other | | Categories | AI Agents, Developer Tools | AI Agents, Developer Tools | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [agents-from-scratch](/tools/pguso-agents-from-scratch.md) | [agor](/tools/preset-io-agor.md) | | --- | --- | --- | | Maintenance | Steady (60%) | Very active (96%) | | Days since push | 56d | 0d | | Open issues (now) | 4 | 219 | | Stars delta | +63 (30d) | +47 (30d) | | Open issues delta | +1 (30d) | -35 (30d) | | Owner type | User | Organization | | Full report | [trust report](/tools/pguso-agents-from-scratch/trust.md) | [trust report](/tools/preset-io-agor/trust.md) | ## 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. ## Decision facts: agor - **Adopt for:** Agor is a team-centric development platform built for orchestrating AI agents in coding and collaboration tasks. ## Choose when ### Choose agents-from-scratch if… - agents-from-scratch is primarily Python; agor is TypeScript. - License: agents-from-scratch is MIT, agor is Other. - 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. - 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. ### Choose agor if… - agor is primarily TypeScript; agents-from-scratch is Python. - License: agor is Other, agents-from-scratch is MIT. - Tags unique to agor: agent-orchestration, agentic, ai-coding, coding-assistant. - agor ships Docker support for self-hosted deployment. - Use Agor if your project requires real-time collaboration and orchestration of multiple AI agents such as Codex and Claude. ## 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. ## When NOT to use agor - Avoid using Agor if your team is not adept at managing AI-driven development workflows and does not require real-time collaboration on a codebase. - Do not opt for Agor when you need standalone coding assistance without the team-centric approach or agent orchestration capabilities. ## Common questions ### What is the difference between agents-from-scratch and agor? agents-from-scratch: Build AI agents locally without relying on frameworks or cloud APIs.. agor: team command center for all things agentic. See the comparison table for live GitHub stats and shared categories. ### When should I choose agents-from-scratch over agor? Choose agents-from-scratch over agor when agents-from-scratch is primarily Python; agor is TypeScript; License: agents-from-scratch is MIT, agor is Other; 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; 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 choose agor over agents-from-scratch? Choose agor over agents-from-scratch when agor is primarily TypeScript; agents-from-scratch is Python; License: agor is Other, agents-from-scratch is MIT; Tags unique to agor: agent-orchestration, agentic, ai-coding, coding-assistant; agor ships Docker support for self-hosted deployment; Use Agor if your project requires real-time collaboration and orchestration of multiple AI agents such as Codex and Claude. ### 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. ### When should I avoid agor? Avoid using Agor if your team is not adept at managing AI-driven development workflows and does not require real-time collaboration on a codebase. Do not opt for Agor when you need standalone coding assistance without the team-centric approach or agent orchestration capabilities. ### Is agents-from-scratch or agor more popular on GitHub? agor has more GitHub stars (1,406 vs 1,017). Stars measure visibility, not whether either tool fits your constraints. ### Are agents-from-scratch and agor open source? Yes - both are open-source projects on GitHub (agents-from-scratch: MIT, agor: Other). ### Where can I find alternatives to agents-from-scratch or agor? GraphCanon lists graph-backed alternatives at [agents-from-scratch alternatives](/tools/pguso-agents-from-scratch/alternatives) and [agor alternatives](/tools/preset-io-agor/alternatives) ([agents-from-scratch markdown twin](/tools/pguso-agents-from-scratch/alternatives.md), [agor markdown twin](/tools/preset-io-agor/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/pguso-agents-from-scratch-vs-preset-io-agor.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, agents-from-scratch or agor? agents-from-scratch: Steady. agor: 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 agents-from-scratch and agor? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [agents-from-scratch trust report](/tools/pguso-agents-from-scratch/trust); [agor trust report](/tools/preset-io-agor/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=pguso-agents-from-scratch`](/api/graphcanon/graph?tool=pguso-agents-from-scratch) - 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/_