--- title: "scrapecraft vs awesome-llm-apps" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/scrapegraphai-scrapecraft-vs-shubhamsaboo-awesome-llm-apps" tools: ["scrapegraphai-scrapecraft", "shubhamsaboo-awesome-llm-apps"] --- # scrapecraft vs awesome-llm-apps *GraphCanon updated Jul 15, 2026* ## Verdict Pick scrapecraft when license: scrapecraft is MIT, awesome-llm-apps is Apache-2.0; pick awesome-llm-apps when license: awesome-llm-apps is Apache-2.0, scrapecraft is MIT. [scrapecraft](https://github.com/ScrapeGraphAI/scrapecraft) reports 671 GitHub stars, 105 forks, and 1 open issues, last pushed Dec 26, 2025. [awesome-llm-apps](https://www.theunwindai.com) has 120k stars, 18k forks, and 17 open issues, last pushed Jul 11, 2026. Figures are from public GitHub metadata via [scrapecraft's repository](https://github.com/ScrapeGraphAI/scrapecraft) and [awesome-llm-apps's repository](https://github.com/Shubhamsaboo/awesome-llm-apps). | | [scrapecraft](/tools/scrapegraphai-scrapecraft.md) | [awesome-llm-apps](/tools/shubhamsaboo-awesome-llm-apps.md) | | --- | --- | --- | | Tagline | 🤖 AI-powered web scraping editor with visual workflow builder. Build, test & deploy web scrapers using natural language. Powered by ScrapeGraphAI & LangGraph. | Over 100 runnable AI Agent and RAG apps to clone, tweak, and deploy. | | Stars | 671 | 119,936 | | Forks | 105 | 17,799 | | Open issues | 1 | 17 | | Language | Python | Python | | Adopt for | - | awesome-llm-apps is a collection of over 100 AI Agent and Retrieval Augmented Generation (RAG) applications that enable users to quickly implement, customize, and deploy practical use cases in Python. | | Persona | - | - | | Runtime | - | - | | License | MIT | The Apache-2.0 license allows users to freely use, modify, and distribute the projects found in awesome-llm-apps under specific conditions outlined by the license. | | Categories | Data & Retrieval, Inference & Serving | AI Agents, Data & Retrieval | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [scrapecraft](/tools/scrapegraphai-scrapecraft.md) | [awesome-llm-apps](/tools/shubhamsaboo-awesome-llm-apps.md) | | --- | --- | --- | | Maintenance | Slowing (36%) | Very active (96%) | | Days since push | 201d | 3d | | Open issues (now) | 1 | 17 | | Owner type | Organization | User | | Full report | [trust report](/tools/scrapegraphai-scrapecraft/trust.md) | [trust report](/tools/shubhamsaboo-awesome-llm-apps/trust.md) | ## Decision facts: awesome-llm-apps - **Pricing:** freemium - Free with open-source licensing, but commercial exploitation is allowed. - **Adopt for:** awesome-llm-apps is a collection of over 100 AI Agent and Retrieval Augmented Generation (RAG) applications that enable users to quickly implement, customize, and deploy practical use cases in Python. - **License detail:** The Apache-2.0 license allows users to freely use, modify, and distribute the projects found in awesome-llm-apps under specific conditions outlined by the license. ## Choose when ### Choose scrapecraft if… - License: scrapecraft is MIT, awesome-llm-apps is Apache-2.0. - Tags unique to scrapecraft: ai, automation, data-extraction, docker. - Also covers Inference & Serving. ### Choose awesome-llm-apps if… - License: awesome-llm-apps is Apache-2.0, scrapecraft is MIT. - Pricing: Free with open-source licensing, but commercial exploitation is allowed.. - Tags unique to awesome-llm-apps: agents, applications, customizable, deployable. - Also covers AI Agents. - When you need quick implementations of various real-world use cases for AI Agents and RAG. ## When NOT to use scrapecraft - Last GitHub push was 201 days ago (slowing maintenance, Dec 26, 2025). Validate activity before betting a new project on scrapecraft. - Data & Retrieval: Skip a heavy ingestion framework when your corpus is small and static; a script plus the embedding API is enough. - Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. ## When NOT to use awesome-llm-apps - If your project requires highly specialized customization beyond what the provided apps can offer out-of-the-box, as deep integration might be required from scratch. - When you are looking for a fully managed service or support directly from developers; this repository is more about self-service and community interaction. ## Common questions ### What is the difference between scrapecraft and awesome-llm-apps? scrapecraft: 🤖 AI-powered web scraping editor with visual workflow builder. Build, test & deploy web scrapers using natural language. Powered by ScrapeGraphAI & LangGraph.. awesome-llm-apps: Over 100 runnable AI Agent and RAG apps to clone, tweak, and deploy.. See the comparison table for live GitHub stats and shared categories. ### When should I choose scrapecraft over awesome-llm-apps? Choose scrapecraft over awesome-llm-apps when License: scrapecraft is MIT, awesome-llm-apps is Apache-2.0; Tags unique to scrapecraft: ai, automation, data-extraction, docker; Also covers Inference & Serving. ### When should I choose awesome-llm-apps over scrapecraft? Choose awesome-llm-apps over scrapecraft when License: awesome-llm-apps is Apache-2.0, scrapecraft is MIT; Pricing: Free with open-source licensing, but commercial exploitation is allowed.; Tags unique to awesome-llm-apps: agents, applications, customizable, deployable; Also covers AI Agents; When you need quick implementations of various real-world use cases for AI Agents and RAG. ### When should I avoid scrapecraft? Last GitHub push was 201 days ago (slowing maintenance, Dec 26, 2025). Validate activity before betting a new project on scrapecraft. Data & Retrieval: Skip a heavy ingestion framework when your corpus is small and static; a script plus the embedding API is enough. Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. ### When should I avoid awesome-llm-apps? If your project requires highly specialized customization beyond what the provided apps can offer out-of-the-box, as deep integration might be required from scratch. When you are looking for a fully managed service or support directly from developers; this repository is more about self-service and community interaction. ### Is scrapecraft or awesome-llm-apps more popular on GitHub? awesome-llm-apps has more GitHub stars (119,936 vs 671). Stars measure visibility, not whether either tool fits your constraints. ### Are scrapecraft and awesome-llm-apps open source? Yes - both are open-source projects on GitHub (scrapecraft: MIT, awesome-llm-apps: Apache-2.0). ### Where can I find alternatives to scrapecraft or awesome-llm-apps? GraphCanon lists graph-backed alternatives at [scrapecraft alternatives](/tools/scrapegraphai-scrapecraft/alternatives) and [awesome-llm-apps alternatives](/tools/shubhamsaboo-awesome-llm-apps/alternatives) ([scrapecraft markdown twin](/tools/scrapegraphai-scrapecraft/alternatives.md), [awesome-llm-apps markdown twin](/tools/shubhamsaboo-awesome-llm-apps/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/scrapegraphai-scrapecraft-vs-shubhamsaboo-awesome-llm-apps.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, scrapecraft or awesome-llm-apps? scrapecraft: Slowing. awesome-llm-apps: 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 scrapecraft and awesome-llm-apps? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [scrapecraft trust report](/tools/scrapegraphai-scrapecraft/trust); [awesome-llm-apps trust report](/tools/shubhamsaboo-awesome-llm-apps/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=scrapegraphai-scrapecraft`](/api/graphcanon/graph?tool=scrapegraphai-scrapecraft) - 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/_