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Works with

Claude CodeClaude DesktopCursorVS CodeClineCodex CLIOpenClaw+ any MCP client

Install to Claude Code

This server doesn't publish a one-line install command. Follow the setup in the source repository.

Summary

Enables AI assistants to manage employee leave by checking balances, applying for leave, and viewing history via MCP tools.

README.md

Leave Management System using MCP (Model Context Protocol)

A minimal, AI-ready Leave Management System built using FastMCP (Model Context Protocol). This project demonstrates how backend business logic can be exposed directly to AI clients (like Claude Desktop), without REST APIs or prompt hacks.

---

✨ Why This Project Exists

Most of us:

  • Watch reels
  • Save YouTube tutorials
  • Bookmark blogs

…but never execute.

This project started when I searched:

“fast api backend for employee management system”

and found this Medium article: 👉 Building a Leave Management System with FastAPI and FastMCP by Madhuri

Instead of just reading it, I asked:

“Why not build it myself?”

That curiosity turned into execution — and this repo is the result.

---

🧠 What This Project Demonstrates

  • What MCP (Model Context Protocol) actually looks like in practice
  • How AI models can discover and call backend functions
  • How to build an AI-first backend, not just an API
  • How Claude Desktop interacts with real application logic

---

⚙️ Features

MCP Tools

  • get_leave_balance(employee_id)
  • apply_leave(employee_id, leave_dates)
  • get_leave_history(employee_id)

MCP Resource

  • greeting://{name}

System Details

  • In-memory mock database
  • Claude Desktop compatible (stdio-based MCP server)
  • No REST APIs, no frontend — pure MCP

---

🏗️ Project Structure

leave-manager-mcp/ ├── main.py # MCP server (Claude-compatible) ├── requirements.txt # Dependencies └── README.md

yaml Copy code

---

▶️ How It Works (Big Picture)

Claude Desktop ↓ Model Context Protocol (MCP) ↓ FastMCP Server (Python) ↓ Business Logic (Leave Management)

yaml Copy code

Claude discovers tools, understands their schema, and calls them directly.

---

🚀 Getting Started

1️⃣ Create & activate virtual environment

python -m venv .venv
source .venv/bin/activate     # Windows: .venv\Scripts\activate
2️⃣ Install dependencies
bash
Copy code
pip install -r requirements.txt
3️⃣ Run MCP server (manual testing)
bash
Copy code
python main.py
⚠️ For Claude Desktop, Claude itself starts this process via MCP configuration.

🤖 Claude Desktop Configuration (Windows Example)
json
Copy code
{
  "mcpServers": {
    "LeaveManagerPython": {
      "command": "C:\\Users\\<USERNAME>\\path\\to\\.venv\\Scripts\\python.exe",
      "args": [
        "C:\\Users\\<USERNAME>\\path\\to\\main.py"
      ],
      "cwd": "C:\\Users\\<USERNAME>\\path\\to\\leave-manager-mcp"
    }
  }
}
🔁 Restart Claude Desktop after updating the config.

🧪 Example Prompts (Claude)
rust
Copy code
Check leave balance for employee E001
Apply leave for employee E002 on 2025-04-17 and 2025-04-18
Show leave history of E001
Use greeting://Akash
Claude will automatically call the correct MCP tools.

⚠️ Key Learnings
MCP requires a pure stdio process

FastAPI & MCP must be separated

Claude Desktop caches MCP configs aggressively

Execution teaches more than tutorials

🔮 Future Improvements
Add FastAPI (dual-mode: REST + MCP)

Persist data using PostgreSQL

Add authentication & roles

Build AI agents on top of MCP tools

Production deployment

📌 Final Thought
Reading tutorials gives comfort.
Watching reels gives motivation.

But execution gives clarity.

This repo exists because of curiosity — not perfection.

yaml
Copy code

---

## ✅ Why This README Works

✔ Clean headings  
✔ Clear story hook  
✔ Explains MCP simply  
✔ Recruiter / dev friendly  
✔ Medium-article ready  
✔ No fluff, no noise  

---

### 🚀 Next (Recommended)
Now that GitHub is ready, next we should:
1. **Write the Medium article using this repo**
2. **Add FastAPI back cleanly (dual-mode)**
3. **Create an AI agent on top of this**

Just say **which one** and we continue 🔥

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