Practical LLM Apps
Clone-and-run AI agents, RAG apps, and MCP servers.
Hand-built examples you can customize and ship — not slide-deck demos.
Works with OpenAI, and several apps run fully local with no API key.
Run one now
Invoice Follow-up Agent
git clone https://github.com/nimish14/practical-llm-apps.git
cd practical-llm-apps/starter_ai_agents/invoice_followup_agent
pip install -r requirements.txt
cp .env.example .env # add OPENAI_API_KEY
streamlit run app.py
Chat with PDF
cd practical-llm-apps/starter_ai_agents/chat_with_pdf
pip install -r requirements.txt
cp .env.example .env # add OPENAI_API_KEY
streamlit run app.py
Resume Evidence RAG (no API key)
cd practical-llm-apps/rag_apps/resume_evidence_rag
pip install -r requirements.txt
streamlit run app.py
Freelance Ops MCP (Cursor / Claude)
cd practical-llm-apps/mcp_servers/freelance-ops-mcp
npm install
npm run build
npx -y @modelcontextprotocol/inspector node dist/index.js
Add to Cursor MCP settings:
{
"mcpServers": {
"freelance-ops": {
"command": "npx",
"args": ["-y", "freelance-ops-mcp"]
}
}
}
(After npm publish — until then, point args at node + local dist/index.js.)
Browse templates
Starter AI Agents
RAG Apps
MCP Servers
Project goals
- Every app: clone → install → run in under 2 minutes
- Clear README with problem, pipeline, and limits
- MCP servers packaged for npm + MCP Registry
- Prefer small, focused tools over mega-frameworks
License
MIT — fork it, ship it, sell it.