AI HR Leave Management Server

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 → Tools

Tech 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.py

Setup

1. Install dependencies

pip install -r requirements.txt

2. 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=8000

3. Run Backend

python backend/app.py

4. Run Frontend

streamlit run frontend/app.py

MCP Tools

Tool	Description
apply_leave	Apply leave request
check_leave_balance	Check remaining leaves
get_leave_history	Past leave records
cancel_leave	Cancel last leave
get_holidays	Upcoming holidays
get_employee_info	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