Leave Management MCP Server

Overview

This project delivers a Model Context Protocol (MCP) server called LeaveManagementSystem. It lets AI assistants such as Cursor or Claude act like an HR co-pilot: gathering leave details, validating policies, instantly approving requests, and emitting human-friendly confirmations. The server is implemented in Python with fastmcp, so it is lightweight, stateful, and easy to extend.

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.

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

Quick Start

Install dependencies (uses uv for deterministic environments):
```
uv pip install -r pyproject.toml
```
Run the MCP server manually (optional):
```
uv run --with mcp[cli] mcp run main.py
```

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

Restart your client to load the new server.

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

MCP Servers