Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@AI HR Leave Management MCP ServerHow many vacation days do I have left?"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
AI HR Leave Management Chatbot
Real MCP Protocol + Groq LLM + FastAPI + Streamlit A real MCP (Model Context Protocol) based HR chatbot using Groq LLM + FastAPI + Streamlit.
Architecture
User → Streamlit → FastAPI → Groq LLM → MCP Client → MCP Server → ToolsTech Stack
MCP SDK — Real stdio transport protocol
Groq LLM — llama-3.3-70b-versatile
FastAPI — Backend REST API
Streamlit — Frontend UI
Project Structure
mcp_chatbot/
├── .env
├── requirements.txt
├── mcp_server/server.py ← MCP Tools
├── backend/agent.py ← MCP Client + Groq
├── backend/app.py ← FastAPI
├── frontend/app.py ← Streamlit UI
└── utils/config.pySetup
1. Install dependencies
pip install -r requirements.txt2. Configure .env
GROQ_API_KEY=your_groq_api_key_here
GROQ_MODEL=llama-3.3-70b-versatile
FASTAPI_HOST=127.0.0.1
FASTAPI_PORT=80003. Run Backend
python backend/app.py4. Run Frontend
streamlit run frontend/app.pyMCP Tools
Tool | Description |
| Apply leave request |
| Check remaining leaves |
| Past leave records |
| Cancel last leave |
| Upcoming holidays |
| Employee details |
Step 4 — Initialize and push bashgit init git add . git commit -m "Initial commit - AI HR MCP Chatbot" git branch -M main git remote add origin https://github.com/anjalimahapatra2004/mcp_tool.git git push -u origin main
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