
Awesome LLM Apps
100+ open-source AI agents, agent skills, and RAG apps — ~140k stars.
About
ShubhamSaboo/awesome-llm-apps is one of GitHub's most-starred AI collections at roughly 140,000 stars: a hand-built, end-to-end-tested library of 100+ open-source AI agents, agent skills, and RAG applications. Unlike link-dump awesome lists, each entry is a complete runnable project — starter AI agents, advanced multi-agent teams, voice AI agents, and crucially an agent_skills/ directory of real installable Claude skills indexed on skills.sh. Everything is Apache-2.0 licensed and organized as clone-and-run tutorials.
For Neuricon's purposes it's both a skill source and a learning resource: the agent-skills section is exactly the installable-skill content the catalog tracks, while the RAG and voice-agent examples serve as working references. Caveat: with 100+ projects, maintenance is uneven — some examples pin model versions that providers later retire, so check the README dates before cloning something six months stale.
What it can do
- 100+ runnable AI agent projects (starter to advanced multi-agent)
- Installable agent skills directory indexed on skills.sh
- Voice AI agent examples with live interaction
- RAG applications with tested end-to-end setups
- Apache-2.0 licensed, community-contributed templates
Setup
Browse the repo at github.com/Shubhamsaboo/awesome-llm-apps, pick a project folder, and follow its README — typically clone, pip install requirements, set API keys in .env, and run. Agent skills install via skills.sh or the npx skills add flow.
Prerequisites
Git, Python 3, and API keys for the model providers each app uses.
Use cases
Works with
Trust score — 9/10
Scored 9/10 (verified tier, metrics-v1). Evidence: Verified via vendor site/docs/GitHub and reputable coverage, wave 68; Trending score 92/100 from researcher assessment.
★ 140,000 GitHub stars
Sources
Every fact above was checked against these sources. Where a claim comes from the provider and couldn't be independently verified, the text says so.