MCP Servers

AI HR Leave Management MCP Server

Provides tools for managing human resources tasks such as applying for leave, checking leave balances, and viewing holiday schedules. It enables natural language interaction for employee information and leave history tracking via the Model Context Protocol.

README

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 → 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

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