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LeaveManager

A Model Context Protocol server that enables users to manage employee leave through natural language. It provides tools to check leave balances, apply for leave, and view leave history via Claude integration.

Updated
Jan 24, 2026

LeaveManager – MCP Server with Claude Integration

LeaveManager is a custom Model Context Protocol (MCP) server built using FastMCP.
It allows Claude to interact with a backend Leave Management System using natural language.

This project demonstrates how Claude can automatically select and execute backend tools based on user queries.


🚀 Features

  • Check employee leave balance
  • Apply leave for specific dates
  • View leave history
  • In-memory state management
  • Claude Desktop integration via MCP
  • Automatic tool selection from natural language

🧠 Tech Stack

  • Python 3.10+
  • FastMCP
  • MCP CLI
  • Claude Desktop (for tool invocation)
  • uv (Python package manager)

📂 Project Structure

my-first-mcp-server/ │ ├── main.py ├── pyproject.toml ├── README.md ├── .gitignore ├── uv.lock └── .venv/


🛠️ MCP Tools

1️⃣ get_leave_balance

Checks remaining leave days for an employee.

Input:

  • employee_id (string)

2️⃣ apply_leave

Applies leave for given dates and updates balance.

Input:

  • employee_id (string)
  • leave_dates (list of YYYY-MM-DD)

3️⃣ get_leave_history

Returns all leave dates taken by an employee.

Input:

  • employee_id (string)

💡 Example Claude Queries

  • “Check leave balance for employee E001”
  • “Apply leave for employee E001 on 2025-04-17 and 2025-05-01”
  • “Show leave history for employee E001”

Claude automatically selects and executes the correct MCP tool.


⚠️ Important Note on Data Storage

  • This project uses in-memory storage
  • Data resets when the MCP server restarts
  • This is intentional for simplicity
  • Can be extended with SQLite for persistence

▶️ Running Locally (Without Claude)

uv run main.py


🎯 Learning Outcomes

Built a real MCP server

Exposed backend tools to Claude

Understood stateful MCP behavior

Integrated Python backend with LLM tool calling

📌 Future Improvements

SQLite persistence

Date validation & duplicate checks

Employee creation & reset tools

FastAPI + MCP hybrid architecture

🧑‍💻 Author

Uma Maheswara Rao
Aspiring AI Engineer / Data Analyst

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