--- title: "prompts.chat vs agents-from-scratch" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/f-prompts-chat-vs-pguso-agents-from-scratch" tools: ["f-prompts-chat", "pguso-agents-from-scratch"] --- # prompts.chat vs agents-from-scratch *GraphCanon updated Sep 20, 2026* ## Verdict Pick prompts.chat if prompts.chat is a platform for sharing and discovering prompts for AI models like ChatGPT, Claude, Gemini, and GPT-4, supporting self-hosting with custom branding, themes, and authentication; 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. [prompts.chat](https://prompts.chat) reports 171k GitHub stars, 22k forks, and 79 open issues, last pushed Sep 9, 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 [prompts.chat's repository](https://github.com/f/prompts.chat) and [agents-from-scratch's repository](https://github.com/pguso/agents-from-scratch). | | [prompts.chat](/tools/f-prompts-chat.md) | [agents-from-scratch](/tools/pguso-agents-from-scratch.md) | | --- | --- | --- | | Tagline | Share, discover, and collect prompts from the community | Build AI agents locally without relying on frameworks or cloud APIs. | | Stars | 170,621 | 1,017 | | Forks | 21,933 | 251 | | Open issues | 79 | 4 | | Language | HTML | Python | | Adopt for | prompts.chat is a platform for sharing and discovering prompts for AI models like ChatGPT, Claude, Gemini, and GPT-4, supporting self-hosting with custom branding, themes, and authentication. | 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 | Other | MIT License: Permissive licensing allowing free use and distribution for both commercial and non-commercial purposes. | | Categories | Developer Tools | AI Agents, Developer Tools | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [prompts.chat](/tools/f-prompts-chat.md) | [agents-from-scratch](/tools/pguso-agents-from-scratch.md) | | --- | --- | --- | | Maintenance | Active (82%) | Steady (60%) | | Days since push | 8d | 56d | | Open issues (now) | 79 | 4 | | Stars delta | +3.4k (30d) | +63 (30d) | | Open issues delta | +14 (30d) | +1 (30d) | | Full report | [trust report](/tools/f-prompts-chat/trust.md) | [trust report](/tools/pguso-agents-from-scratch/trust.md) | ## Decision facts: prompts.chat - **Pricing:** freemium - The platform is free and open source, allowing for self-hosting with complete privacy. However, users may need to pay for hosting and database services. - **Requirements:** Min 2 GB RAM; Requires Docker; Requires PostgreSQL for database management.; Supports self-hosting with custom branding, themes, and authentication. - **Adopt for:** prompts.chat is a platform for sharing and discovering prompts for AI models like ChatGPT, Claude, Gemini, and GPT-4, supporting self-hosting with custom branding, themes, and authentication. ## 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 prompts.chat if… - prompts.chat is primarily HTML; agents-from-scratch is Python. - License: prompts.chat is Other, agents-from-scratch is MIT. - Pricing: The platform is free and open source, allowing for self-hosting with complete privacy. However, users may need to pay for hosting and database services.. - Requirements: Min 2 GB RAM; Requires Docker; Requires PostgreSQL for database management.; Supports self-hosting with custom branding, themes, and authentication.. - Tags unique to prompts.chat: ai, artificial-intelligence, awesome-list, chatgpt. - prompts.chat ships an MCP server manifest. - When you need a platform that supports self-hosting with complete privacy and customization options like custom branding, themes, and authentication methods. ### Choose agents-from-scratch if… - agents-from-scratch is primarily Python; prompts.chat is HTML. - License: agents-from-scratch is MIT, prompts.chat 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. - 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 NOT to use prompts.chat - If you are looking for a platform that does not require self-hosting and prefer a fully managed service without the need for setup and maintenance. - When your organization does not have the technical capability to set up and maintain a PostgreSQL database, which is recommended for use with prompts.chat. ## 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 prompts.chat and agents-from-scratch? prompts.chat: Share, discover, and collect prompts from the community. 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 prompts.chat over agents-from-scratch? Choose prompts.chat over agents-from-scratch when prompts.chat is primarily HTML; agents-from-scratch is Python; License: prompts.chat is Other, agents-from-scratch is MIT; Pricing: The platform is free and open source, allowing for self-hosting with complete privacy. However, users may need to pay for hosting and database services.; Requirements: Min 2 GB RAM; Requires Docker; Requires PostgreSQL for database management.; Supports self-hosting with custom branding, themes, and authentication.; Tags unique to prompts.chat: ai, artificial-intelligence, awesome-list, chatgpt; prompts.chat ships an MCP server manifest; When you need a platform that supports self-hosting with complete privacy and customization options like custom branding, themes, and authentication methods. ### When should I choose agents-from-scratch over prompts.chat? Choose agents-from-scratch over prompts.chat when agents-from-scratch is primarily Python; prompts.chat is HTML; License: agents-from-scratch is MIT, prompts.chat 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; 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 avoid prompts.chat? If you are looking for a platform that does not require self-hosting and prefer a fully managed service without the need for setup and maintenance. When your organization does not have the technical capability to set up and maintain a PostgreSQL database, which is recommended for use with prompts.chat. ### 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 prompts.chat or agents-from-scratch more popular on GitHub? prompts.chat has more GitHub stars (170,621 vs 1,017). Stars measure visibility, not whether either tool fits your constraints. ### Are prompts.chat and agents-from-scratch open source? Yes - both are open-source projects on GitHub (prompts.chat: Other, agents-from-scratch: MIT). ### Where can I find alternatives to prompts.chat or agents-from-scratch? GraphCanon lists graph-backed alternatives at [prompts.chat alternatives](/tools/f-prompts-chat/alternatives) and [agents-from-scratch alternatives](/tools/pguso-agents-from-scratch/alternatives) ([prompts.chat markdown twin](/tools/f-prompts-chat/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/f-prompts-chat-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, prompts.chat or agents-from-scratch? prompts.chat: 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 prompts.chat and agents-from-scratch? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [prompts.chat trust report](/tools/f-prompts-chat/trust); [agents-from-scratch trust report](/tools/pguso-agents-from-scratch/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=f-prompts-chat`](/api/graphcanon/graph?tool=f-prompts-chat) - 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/_