Shubhamsaboo/awesome-llm-apps
This Apache-2.0 collection provides runnable agent, skill, MCP, memory, multi-agent, and RAG examples across major model providers, useful for borrowing patterns before choosing a stack.
The repository collects **100+ open-source** agents, skills, and RAG apps under **Apache-2.0**. Examples span single-file agents, production-style tool loops, background jobs, multi-agent teams, voice, generative UI, MCP, memory, and retrieval.
Use it as a pattern library: run the smallest example matching your problem, inspect its tool and state boundaries, then transplant only the useful plumbing. Provider coverage includes Claude, Gemini, GPT, DeepSeek, Llama, and Qwen.
The repository collects **100+ open-source** agents, skills, and RAG apps under **Apache-2.0**. Examples span single-file agents, production-style tool loops, background jobs, multi-agent teams, voice, generative UI, MCP, memory, and retrieval. Use it as a pattern library: run the smallest example matching your problem, inspect its tool and state boundaries, then transplant only the useful plumbing. Provider coverage includes Claude, Gemini, GPT, DeepSeek, Llama, and Qwen. Breadth is not production validation. The material says skills pass a security and eval CI gate, but provides no comparable reliability results for the wider app catalog; sensitive medical, financial, and mental-health examples need independent controls.
This broadens the available design space for agents, skills, retrieval, memory, and tool loops, but changes discovery more than confidence: the catalog is useful for locating minimal reference implementations, not for inferring production readiness. Its stated skill gates provide a narrower trust signal than the repository’s breadth, leaving sensitive examples dependent on independent evaluation and controls.