Leavemanagementmcp

🚀 Leave Management MCP Server

This project offers a Model Context Protocol (MCP) server named LeaveManagementSystem, enabling AI assistants like Cursor or Claude to function as HR co - pilots. They can gather leave details, validate policies, approve requests instantly, and send user - friendly confirmations. The server, implemented in Python with fastmcp, is lightweight, stateful, and easily extensible.

🚀 Quick Start

1. Install dependencies (uses uv for deterministic environments):

   uv pip install -r pyproject.toml
   

2. Run the MCP server manually (optional):

   uv run --with mcp[cli] mcp run main.py
   

3. Register the server in your MCP client (Cursor or Claude). Use the command:

   C:\Users\Asus\.local\bin\uv.EXE run --with mcp[cli] mcp run C:\Users\Asus\Desktop\leavemanagementMCP\main.py
   

4. Restart your client to load the new server.

✨ Features

The Problem We Solve

• Manual leave workflows are slow. HR teams spend time collecting employee information, validating policies, and writing approval emails.
• Assistants often miss critical context. Typical AI automations trigger tools without ensuring they have all details, leading to errors or back - and - forth clarification.
• Approvals need an auditable trail. Managers want visibility into who asked for leave, how many days have been taken, and why the leave was granted.

Solution Highlights

• Structured MCP tools: apply_leave, approve_leave, reject_leave, and the leave - status resource expose all core HR actions as deterministic APIs.
• Guardrails built in: Tool validation ensures the assistant collects employee_id, days, and a concrete reason before taking action.
• Auto - approval workflow: When apply_leave is invoked, the system automatically approves the request, updates balances, and simulates an email notification. Claude (or any MCP - aware assistant) can respond instantly without waiting for a human manager.
• Live status tracking: Assistants can query leave - status://{emp_id} to share current balances and decision history with employees.

Why This Is Cutting Edge

• Assistant - first design: Instead of exposing yet another REST API, we deliver a native MCP server tailored for LLM tooling platforms. Claude, Cursor, and future MCP clients can discover capabilities, enforce parameter contracts, and orchestrate advanced flows with minimal glue code.
• Operational safety for AI agents: Validation, policy limits, and audit trails are enforced server - side, making it safer to let autonomous agents approve leave.
• Composable HR automations: Because everything runs inside an MCP server, you can chain this with other MCP services—calendar syncing, payroll, analytics—without bespoke integrations.
• Ready for real - time collaboration: The in - memory model keeps state during the session; migrating to a database or SaaS backend is as simple as swapping out the storage layer.

📚 Documentation

Tech Stack

Core Technologies

• Python 3.11+: Modern Python with type hints for robust development
• FastMCP: High - performance MCP server framework that provides seamless integration with MCP - compatible clients
• Model Context Protocol (MCP): Standardized protocol for AI assistants to interact with external tools and resources
• uv: Fast Python package installer and dependency manager for reproducible environments

Data Layer

• Current Implementation: In - memory data structures (dictionaries and lists) for rapid prototyping and development
• Production Ready: Designed with database abstraction in mind—can seamlessly connect to:
  • SQLite: Lightweight, file - based database for small to medium deployments
  • PostgreSQL: Enterprise - grade relational database for production environments
  • MySQL/MariaDB: Alternative relational database options
  • MongoDB: NoSQL option for flexible document storage
  • SaaS HRIS APIs: Direct integration with existing HR management systems (Workday, BambooHR, etc.)

Integration Points

• MCP Clients: Native support for Claude Desktop, Cursor IDE, and any MCP - compatible client
• Email Notifications: Simulated email system (ready for integration with SendGrid, AWS SES, SMTP servers)
• Future Extensions: Calendar APIs, Slack/Teams webhooks, payroll systems

Development Tools

• pyproject.toml: Modern Python project configuration with dependency management
• uv.lock: Locked dependency versions for reproducible builds

Architecture At a Glance

Claude / Cursor ──► MCP Transport ──► LeaveManagementSystem (fastmcp)
                                   ├─ apply_leave()  → Validates → Approves → Sends notification
                                   ├─ approve_leave() → Manual override
                                   ├─ reject_leave()  → Manual override
                                   └─ leave - status resource → Generates human - readable summaries
                                   
Data Layer (Configurable):
├─ In - Memory (Development) ──► Python dictionaries/lists
└─ Database (Production) ───► SQLite / PostgreSQL / MySQL / MongoDB / HRIS APIs

Using the Server

• Apply for leave: Collect emp_id, days, and reason. The tool auto - approves and returns a formatted confirmation plus a simulated email notification.
• Override decisions: If needed, call approve_leave or reject_leave manually to adjust status.
• Check status: Query leave - status://emp001 (replace with any employee) to see balances and decision history.

Extending the System

Database Integration

The system is architected to support direct database connections. You can replace the in - memory data structures with database queries:

• SQLite: Perfect for small teams, single - file database with zero configuration
• PostgreSQL/MySQL: Enterprise - ready with ACID compliance, transactions, and complex queries
• MongoDB: Document - based storage for flexible schema evolution
• HRIS APIs: Connect directly to existing HR systems (Workday, BambooHR, ADP) via REST/GraphQL APIs

Example database integration pattern:

# Replace in - memory dictionaries with database queries
employees = db.query("SELECT emp_id, name, leaves_taken FROM employees")
leave_requests = db.query("SELECT * FROM leave_requests WHERE emp_id = ?", [emp_id])

Additional Enhancements

• Authentication & Authorization: Add role - based access control (RBAC) to restrict who can approve/reject leaves
• Real Email/SMS Integration: Connect to transactional email providers (SendGrid, AWS SES) or SMS gateways (Twilio)
• Analytics & Reporting: Expose MCP resources for year - to - date summaries, team leave calendars, and policy compliance reports
• Webhook Support: Trigger external systems when leaves are approved/rejected
• Multi - tenant Support: Isolate data by organization/company for SaaS deployments