--- title: "End-to-End-Agentic-Ai-Automation-Lab vs awesome-ai-apps" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/mdalamin5-end-to-end-agentic-ai-automation-lab-vs-rohitg00-awesome-ai-apps" tools: ["mdalamin5-end-to-end-agentic-ai-automation-lab", "rohitg00-awesome-ai-apps"] --- # End-to-End-Agentic-Ai-Automation-Lab vs awesome-ai-apps *GraphCanon updated Sep 20, 2026* ## Verdict Pick End-to-End-Agentic-Ai-Automation-Lab if end-to-End-Agentic-Ai-Automation-Lab offers hands-on projects and code for multi-agent systems using technologies like LangChain, AutoGen, CrewAI, RAG, MCP, and n8n on Docker, AWS, BentoML; pick awesome-ai-apps if awesome-ai-apps offers curated AI application examples with diverse tech stacks including OpenAI, Gemini, and local models. [End-to-End-Agentic-Ai-Automation-Lab](https://www.linkedin.com/in/mdalamin5/) reports 97 GitHub stars, 39 forks, and 0 open issues, last pushed Jun 11, 2026. [awesome-ai-apps](https://agenstskills.com) has 828 stars, 177 forks, and 33 open issues, last pushed Feb 10, 2026. Figures are from public GitHub metadata via [End-to-End-Agentic-Ai-Automation-Lab's repository](https://github.com/MDalamin5/End-to-End-Agentic-Ai-Automation-Lab) and [awesome-ai-apps's repository](https://github.com/rohitg00/awesome-ai-apps). | | [End-to-End-Agentic-Ai-Automation-Lab](/tools/mdalamin5-end-to-end-agentic-ai-automation-lab.md) | [awesome-ai-apps](/tools/rohitg00-awesome-ai-apps.md) | | --- | --- | --- | | Tagline | Hands-on projects and code examples for multi-agent systems | A curated collection of AI Agents and LLM Apps with various tech stacks | | Stars | 97 | 828 | | Forks | 39 | 177 | | Open issues | 0 | 33 | | Language | Jupyter Notebook | HTML | | Adopt for | End-to-End-Agentic-Ai-Automation-Lab offers hands-on projects and code for multi-agent systems using technologies like LangChain, AutoGen, CrewAI, RAG, MCP, and n8n on Docker, AWS, BentoML. | awesome-ai-apps offers curated AI application examples with diverse tech stacks including OpenAI, Gemini, and local models. | | Persona | - | - | | Runtime | - | - | | License | MIT | Apache-2.0 | | Categories | AI Agents, LLM Frameworks | AI Agents, LLM Frameworks | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [End-to-End-Agentic-Ai-Automation-Lab](/tools/mdalamin5-end-to-end-agentic-ai-automation-lab.md) | [awesome-ai-apps](/tools/rohitg00-awesome-ai-apps.md) | | --- | --- | --- | | Days since push | 92d | 221d | | Open issues (now) | 0 | 33 | | Stars delta | +7 (30d) | +11 (30d) | | Open issues delta | 0 (30d) | +6 (30d) | | Full report | [trust report](/tools/mdalamin5-end-to-end-agentic-ai-automation-lab/trust.md) | [trust report](/tools/rohitg00-awesome-ai-apps/trust.md) | ## Decision facts: End-to-End-Agentic-Ai-Automation-Lab - **Adopt for:** End-to-End-Agentic-Ai-Automation-Lab offers hands-on projects and code for multi-agent systems using technologies like LangChain, AutoGen, CrewAI, RAG, MCP, and n8n on Docker, AWS, BentoML. ## Decision facts: awesome-ai-apps - **Adopt for:** awesome-ai-apps offers curated AI application examples with diverse tech stacks including OpenAI, Gemini, and local models. ## Choose when ### Choose End-to-End-Agentic-Ai-Automation-Lab if… - End-to-End-Agentic-Ai-Automation-Lab is primarily Jupyter Notebook; awesome-ai-apps is HTML. - License: End-to-End-Agentic-Ai-Automation-Lab is MIT, awesome-ai-apps is Apache-2.0. - Tags unique to End-to-End-Agentic-Ai-Automation-Lab: agentic-ai, autogen, aws, bentoml. - For developing complex multi-agent systems with automated workflows ### Choose awesome-ai-apps if… - awesome-ai-apps is primarily HTML; End-to-End-Agentic-Ai-Automation-Lab is Jupyter Notebook. - License: awesome-ai-apps is Apache-2.0, End-to-End-Agentic-Ai-Automation-Lab is MIT. - Tags unique to awesome-ai-apps: agents, ai, apps, automation. - For exploring real-world implementations of AI agents across different technologies ## When NOT to use End-to-End-Agentic-Ai-Automation-Lab - If your project does not involve multi-agent systems or automation layers like n8n - If you are looking for a simpler introductory tool to AI without the focus on deployment details ## When NOT to use awesome-ai-apps - When seeking detailed implementation steps specific to one technology stack - In scenarios demanding a deep dive into proprietary or less publicly-known application codes ## Common questions ### What is the difference between End-to-End-Agentic-Ai-Automation-Lab and awesome-ai-apps? End-to-End-Agentic-Ai-Automation-Lab: Hands-on projects and code examples for multi-agent systems. awesome-ai-apps: A curated collection of AI Agents and LLM Apps with various tech stacks. See the comparison table for live GitHub stats and shared categories. ### When should I choose End-to-End-Agentic-Ai-Automation-Lab over awesome-ai-apps? Choose End-to-End-Agentic-Ai-Automation-Lab over awesome-ai-apps when End-to-End-Agentic-Ai-Automation-Lab is primarily Jupyter Notebook; awesome-ai-apps is HTML; License: End-to-End-Agentic-Ai-Automation-Lab is MIT, awesome-ai-apps is Apache-2.0; Tags unique to End-to-End-Agentic-Ai-Automation-Lab: agentic-ai, autogen, aws, bentoml; For developing complex multi-agent systems with automated workflows. ### When should I choose awesome-ai-apps over End-to-End-Agentic-Ai-Automation-Lab? Choose awesome-ai-apps over End-to-End-Agentic-Ai-Automation-Lab when awesome-ai-apps is primarily HTML; End-to-End-Agentic-Ai-Automation-Lab is Jupyter Notebook; License: awesome-ai-apps is Apache-2.0, End-to-End-Agentic-Ai-Automation-Lab is MIT; Tags unique to awesome-ai-apps: agents, ai, apps, automation; For exploring real-world implementations of AI agents across different technologies. ### When should I avoid End-to-End-Agentic-Ai-Automation-Lab? If your project does not involve multi-agent systems or automation layers like n8n If you are looking for a simpler introductory tool to AI without the focus on deployment details ### When should I avoid awesome-ai-apps? When seeking detailed implementation steps specific to one technology stack In scenarios demanding a deep dive into proprietary or less publicly-known application codes ### Is End-to-End-Agentic-Ai-Automation-Lab or awesome-ai-apps more popular on GitHub? awesome-ai-apps has more GitHub stars (828 vs 97). Stars measure visibility, not whether either tool fits your constraints. ### Are End-to-End-Agentic-Ai-Automation-Lab and awesome-ai-apps open source? Yes - both are open-source projects on GitHub (End-to-End-Agentic-Ai-Automation-Lab: MIT, awesome-ai-apps: Apache-2.0). ### Where can I find alternatives to End-to-End-Agentic-Ai-Automation-Lab or awesome-ai-apps? GraphCanon lists graph-backed alternatives at [End-to-End-Agentic-Ai-Automation-Lab alternatives](/tools/mdalamin5-end-to-end-agentic-ai-automation-lab/alternatives) and [awesome-ai-apps alternatives](/tools/rohitg00-awesome-ai-apps/alternatives) ([End-to-End-Agentic-Ai-Automation-Lab markdown twin](/tools/mdalamin5-end-to-end-agentic-ai-automation-lab/alternatives.md), [awesome-ai-apps markdown twin](/tools/rohitg00-awesome-ai-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/mdalamin5-end-to-end-agentic-ai-automation-lab-vs-rohitg00-awesome-ai-apps.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, End-to-End-Agentic-Ai-Automation-Lab or awesome-ai-apps? End-to-End-Agentic-Ai-Automation-Lab: Slowing. awesome-ai-apps: Slowing. 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 End-to-End-Agentic-Ai-Automation-Lab and awesome-ai-apps? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [End-to-End-Agentic-Ai-Automation-Lab trust report](/tools/mdalamin5-end-to-end-agentic-ai-automation-lab/trust); [awesome-ai-apps trust report](/tools/rohitg00-awesome-ai-apps/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=mdalamin5-end-to-end-agentic-ai-automation-lab`](/api/graphcanon/graph?tool=mdalamin5-end-to-end-agentic-ai-automation-lab) - 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/_