--- title: "agents-from-scratch vs grepai" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/pguso-agents-from-scratch-vs-yoanbernabeu-grepai" tools: ["pguso-agents-from-scratch", "yoanbernabeu-grepai"] --- # agents-from-scratch vs grepai *GraphCanon updated Aug 22, 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 grepai if grepai is designed for developing local semantic search and call graphs for AI agents with an emphasis on privacy. [agents-from-scratch](https://github.com/pguso/agents-from-scratch) reports 954 GitHub stars, 240 forks, and 3 open issues, last pushed Jul 25, 2026. [grepai](https://yoanbernabeu.github.io/grepai/) has 1.8k stars, 152 forks, and 97 open issues, last pushed Jun 22, 2026. Figures are from public GitHub metadata via [agents-from-scratch's repository](https://github.com/pguso/agents-from-scratch) and [grepai's repository](https://github.com/yoanbernabeu/grepai). | | [agents-from-scratch](/tools/pguso-agents-from-scratch.md) | [grepai](/tools/yoanbernabeu-grepai.md) | | --- | --- | --- | | Tagline | Build AI agents locally without relying on frameworks or cloud APIs. | Semantic Search & Call Graphs for AI Agents (100% Local) | | Stars | 954 | 1,825 | | Forks | 240 | 152 | | Open issues | 3 | 97 | | Language | Python | C | | 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. | grepai is designed for developing local semantic search and call graphs for AI agents with an emphasis on privacy. | | Persona | - | - | | Runtime | - | - | | License | MIT License: Permissive licensing allowing free use and distribution for both commercial and non-commercial purposes. | MIT license, allowing for wide usage in both open-source and proprietary applications without restrictions on redistribution. | | Categories | AI Agents, Developer Tools | Developer Tools, Vector Databases | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [agents-from-scratch](/tools/pguso-agents-from-scratch.md) | [grepai](/tools/yoanbernabeu-grepai.md) | | --- | --- | --- | | Maintenance | Active (82%) | Steady (60%) | | Days since push | 18d | 61d | | Open issues (now) | 3 | 97 | | Stars delta | Unknown | +36 (30d) | | Open issues delta | Unknown | +1 (30d) | | Full report | [trust report](/tools/pguso-agents-from-scratch/trust.md) | [trust report](/tools/yoanbernabeu-grepai/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: grepai - **Pricing:** freemium - Available at no cost due to its MIT licensing, with the scope of use limited only by any dependencies it requires. - **Adopt for:** grepai is designed for developing local semantic search and call graphs for AI agents with an emphasis on privacy. - **License detail:** MIT license, allowing for wide usage in both open-source and proprietary applications without restrictions on redistribution. ## Choose when ### Choose agents-from-scratch if… - agents-from-scratch is primarily Python; grepai is C. - 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 AI Agents. - 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 grepai if… - grepai is primarily C; agents-from-scratch is Python. - Pricing: Available at no cost due to its MIT licensing, with the scope of use limited only by any dependencies it requires.. - Tags unique to grepai: ai, claude-code, cli, code-search. - Also covers Vector Databases. - When you need to develop a system that prioritizes local processing without cloud dependencies, which is essential in highly regulated environments where data privacy and security are paramount. ## 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 grepai - Not suitable if your application requires real-time updates from cloud-based services, as grepai operates entirely locally without any online components for updating its functionality. - If the development team prefers not to deal with C language implementation details,grepai might be less attractive given that other tools may support more modern or higher-level languages like Python. ## Common questions ### What is the difference between agents-from-scratch and grepai? agents-from-scratch: Build AI agents locally without relying on frameworks or cloud APIs.. grepai: Semantic Search & Call Graphs for AI Agents (100% Local). See the comparison table for live GitHub stats and shared categories. ### When should I choose agents-from-scratch over grepai? Choose agents-from-scratch over grepai when agents-from-scratch is primarily Python; grepai is C; 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 AI Agents; 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 grepai over agents-from-scratch? Choose grepai over agents-from-scratch when grepai is primarily C; agents-from-scratch is Python; Pricing: Available at no cost due to its MIT licensing, with the scope of use limited only by any dependencies it requires.; Tags unique to grepai: ai, claude-code, cli, code-search; Also covers Vector Databases; When you need to develop a system that prioritizes local processing without cloud dependencies, which is essential in highly regulated environments where data privacy and security are paramount. ### 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 grepai? Not suitable if your application requires real-time updates from cloud-based services, as grepai operates entirely locally without any online components for updating its functionality. If the development team prefers not to deal with C language implementation details,grepai might be less attractive given that other tools may support more modern or higher-level languages like Python. ### Is agents-from-scratch or grepai more popular on GitHub? grepai has more GitHub stars (1,825 vs 954). Stars measure visibility, not whether either tool fits your constraints. ### Are agents-from-scratch and grepai open source? Yes - both are open-source projects on GitHub (agents-from-scratch: MIT, grepai: MIT). ### Where can I find alternatives to agents-from-scratch or grepai? GraphCanon lists graph-backed alternatives at [agents-from-scratch alternatives](/tools/pguso-agents-from-scratch/alternatives) and [grepai alternatives](/tools/yoanbernabeu-grepai/alternatives) ([agents-from-scratch markdown twin](/tools/pguso-agents-from-scratch/alternatives.md), [grepai markdown twin](/tools/yoanbernabeu-grepai/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-yoanbernabeu-grepai.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 grepai? agents-from-scratch: Active. grepai: 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 agents-from-scratch and grepai? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [agents-from-scratch trust report](/tools/pguso-agents-from-scratch/trust); [grepai trust report](/tools/yoanbernabeu-grepai/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/_