Flight Simulator MCP Server

An enhanced Model Context Protocol (MCP) server for comprehensive airline booking operations, built with FastMCP 2.0 and Python.

Features

🛫 Core Booking Tools (17 total)

Flight Search & Booking: Multi-criteria search, booking creation, modifications
Check-in & Services: Online check-in, seat selection, baggage, meal preferences
Real-time Operations: Flight tracking, price alerts, disruption handling
Loyalty & Groups: Frequent flyer integration, group bookings, special assistance

📊 Information Resources (9 total)

Airport information with timezones
Real-time flight status
Seat maps and availability
Weather impact data
Airline policies
Gate information
Upgrade availability
Loyalty benefits

🤖 AI-Powered Prompts (6 total)

Intelligent flight search assistance
Complete booking workflow guidance
Multi-city trip planning
Disruption management
Loyalty optimization
Accessibility support

Installation

Prerequisites

Python 3.10 or higher
UV package manager (recommended) or pip

Setup

Clone the repository:

git clone <repository-url>
cd flight-sim-mcp

Install dependencies using UV (recommended):

uv pip install -r requirements.txt

Or using pip:

pip install -r requirements.txt

Copy environment configuration:

cp .env.example .env

Configure your .env file with appropriate values.

Usage

Running the Server

Start the MCP server:

python src/server.py

The server will start in stdio mode by default, suitable for integration with Claude Desktop or other MCP clients.

Integration with Claude Desktop

Open your Claude Desktop configuration file:
- macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
- Windows: %APPDATA%\Claude\claude_desktop_config.json
Add the flight simulator server:

{
  "mcpServers": {
    "flight-simulator": {
      "command": "python",
      "args": ["/path/to/flight-sim-mcp/src/server.py"],
      "env": {}
    }
  }
}

Restart Claude Desktop

Example Interactions

Flight Search:

"Find me a flight from San Francisco to New York next Friday"

Group Booking:

"I need to book flights for 8 people from SFO to JFK on March 15th"

Check-in:

"Check me in for booking BK12345ABC"

Flight Tracking:

"Track flight UA123"

Loyalty Optimization:

"How can I maximize my miles on upcoming trips?"

Available Tools

Flight Search & Booking

search_flights - Search with multiple criteria
get_flight_details - Detailed flight information
create_booking - Book flights
get_booking - Retrieve booking details
cancel_booking - Cancel with refund calculation
modify_booking - Change flights or dates

Check-in & Services

check_in - Online check-in with boarding passes
select_seats - Choose specific seats
add_baggage - Add checked bags
add_services - Meals, WiFi, priority boarding
travel_insurance - Trip protection options
special_assistance - Accessibility services

Real-time & Loyalty

track_flight - Live flight status
price_alert - Monitor price changes
loyalty_account - Link frequent flyer accounts
group_booking - 5+ passenger bookings
upgrade_seat - Request upgrades

Testing

Using MCP Inspector

Install MCP Inspector:

npm install -g @modelcontextprotocol/inspector

Run the inspector:

npx mcp-inspector python src/server.py

Access the web UI at http://localhost:5173

Running Unit Tests

pytest tests/

Development

Project Structure

flight-sim-mcp/
├── src/
│   ├── server.py           # Main MCP server
│   ├── tools/             # Tool implementations
│   ├── resources/         # Resource endpoints
│   ├── models/           # Pydantic data models
│   ├── data/             # Mock database
│   └── prompts/          # AI prompt templates
├── tests/                # Test files
├── pyproject.toml       # Project configuration
└── README.md           # This file

Adding New Tools

Create a new file in src/tools/
Import the MCP instance: from ..server import mcp
Define tools using the @mcp.tool() decorator
Import the module in server.py

Mock Data

The server uses a mock database that generates realistic flight data for demonstrations. In production, this would connect to real airline APIs.

Security Considerations

API tokens should be stored in environment variables
Payment tokens are mocked - implement real payment integration for production
Personal data handling follows privacy best practices
Rate limiting is recommended for production deployments

Deployment

Local Development

The default stdio transport is perfect for local development and testing with Claude Desktop.

Remote Deployment

For remote access, configure SSE transport:

# In server.py or via environment variables
MCP_TRANSPORT=sse
MCP_HOST=0.0.0.0
MCP_PORT=8080

Deploy options:

Docker container (Dockerfile included)
Railway/Render (one-click deploy)
AWS Lambda (serverless)
Any Python-capable hosting platform

Contributing

Fork the repository
Create a feature branch
Add tests for new functionality
Submit a pull request

License

MIT License - see LICENSE file for details

Support

For issues, questions, or contributions:

Open an issue on GitHub
Check existing documentation
Review MCP protocol specs at modelcontextprotocol.io