AMC MCP Server
Provides a comprehensive movie booking experience for AMC Theatres, enabling users to discover movies, find showtimes, select seats, and process payments through conversational AI. Supports multi-location theater search with real-time seat availability and booking management.
README
AMC MCP Server 🎬
An Model Context Protocol (MCP) server that provides a comprehensive movie booking experience for AMC Theatres. This server enables conversational AI assistants to help users discover movies, find showtimes, book seats, and process payments through a simple API interface.
Features ✨
- Movie Discovery: Browse currently showing movies and get personalized recommendations
- Showtime Lookup: Find available showtimes by location, date, and movie
- Seat Selection: View interactive seat maps and check availability
- Booking Management: Reserve seats with real-time availability checking
- Payment Processing: Handle mock payment transactions with confirmation receipts
- Multi-location Support: Search across multiple AMC theater locations
Quick Start 🚀
Prerequisites
- Python 3.8+
- Docker (optional, for containerized deployment)
Installation
Option 1: Local Installation
- Clone the repository:
git clone <repository-url>
cd amc-mcp
- Install dependencies:
pip install -r requirements.txt
- Install the package:
pip install -e .
- Run the server:
python -m amc_mcp.fastmcp_server
Option 2: Docker Deployment
- Build and run with Docker Compose:
docker-compose up --build
- Or build and run manually:
docker build -t amc-mcp .
docker run -it amc-mcp
MCP Tools Reference 🛠️
1. get_now_showing
Returns a list of movies currently showing in a given location.
Input:
{
"location": "Boston, MA"
}
Output:
{
"location": "Boston, MA",
"movies": [
{
"movie_id": "mv001",
"title": "Dune: Part Two",
"rating": "PG-13",
"duration": 166,
"genre": "Sci-Fi/Action",
"description": "Paul Atreides unites with Chani..."
}
]
}
2. get_recommendations
Suggests movies based on mood, genre, or preferences.
Input:
{
"genre": "action",
"mood": "exciting"
}
Output:
{
"criteria": {"genre": "action", "mood": "exciting"},
"recommendations": [...]
}
3. get_showtimes
Fetches available showtimes for a specific movie and location.
Input:
{
"movie_id": "mv001",
"date": "2025-10-28",
"location": "Boston, MA"
}
Output:
{
"movie": {"id": "mv001", "title": "Dune: Part Two"},
"date": "2025-10-28",
"location": "Boston, MA",
"showtimes": [
{
"showtime_id": "st001",
"theater_name": "AMC Boston Common 19",
"theater_address": "175 Tremont Street",
"time": "14:00",
"format": "IMAX",
"price": 18.50
}
]
}
4. get_seat_map
Displays available and reserved seats for a specific showtime.
Input:
{
"showtime_id": "st001"
}
Output:
{
"showtime_id": "st001",
"movie": "Dune: Part Two",
"theater": "AMC Boston Common 19",
"date": "2025-10-28",
"time": "14:00",
"seat_map": [
{
"seat_number": "A5",
"row": "A",
"column": 5,
"is_available": true,
"price_tier": "Standard",
"price": 18.50
}
]
}
5. book_seats
Reserves selected seats for the user.
Input:
{
"showtime_id": "st001",
"seats": ["A5", "A6"],
"user_id": "user123"
}
Output:
{
"booking_id": "booking-uuid",
"status": "pending",
"movie": "Dune: Part Two",
"theater": "AMC Boston Common 19",
"date": "2025-10-28",
"time": "14:00",
"seats": ["A5", "A6"],
"total_price": 37.00
}
6. process_payment
Handles simulated payment transaction.
Input:
{
"booking_id": "booking-uuid",
"payment_method": "card",
"amount": 37.00
}
Output:
{
"payment_id": "payment-uuid",
"payment_status": "success",
"booking_id": "booking-uuid",
"receipt_url": "https://amc.com/receipts/payment-uuid",
"confirmation": {
"movie": "Dune: Part Two",
"theater": "AMC Boston Common 19",
"date": "2025-10-28",
"time": "14:00",
"seats": ["A5", "A6"],
"total_paid": 37.00
}
}
Example Conversation Flow 💬
Here's how a typical movie booking conversation would work:
-
User: "Find an action movie near me tonight."
- Server calls:
get_now_showing+get_recommendations - Returns: List of action movies with showtimes
- Server calls:
-
User: "Book two seats for Dune: Part Two at 8 PM."
- Server calls:
get_showtimes→get_seat_map→book_seats - Returns: Seat selection and booking confirmation
- Server calls:
-
User: "Pay with my card."
- Server calls:
process_payment - Returns: Payment confirmation with digital receipt
- Server calls:
Architecture 🏗️
amc-mcp/
├── src/
│ └── amc_mcp/
│ ├── __init__.py
│ └── server.py # Main MCP server implementation
├── data/
│ ├── movies.json # Movie catalog
│ ├── theaters.json # Theater locations
│ ├── showtimes.json # Showtime schedules
│ └── seats.json # Seat maps by showtime
├── config/
│ └── nginx.conf # Web server configuration
├── Dockerfile # Container configuration
├── docker-compose.yml # Multi-service orchestration
├── requirements.txt # Python dependencies
├── pyproject.toml # Package configuration
└── README.md # This file
Data Models 📊
Movie
{
"movie_id": str,
"title": str,
"rating": str, # PG, PG-13, R, etc.
"duration": int, # Minutes
"genre": str,
"description": str,
"poster_url": str
}
Theater
{
"theater_id": str,
"name": str,
"address": str,
"city": str,
"state": str,
"zip_code": str
}
Showtime
{
"showtime_id": str,
"movie_id": str,
"theater_id": str,
"date": str, # YYYY-MM-DD
"time": str, # HH:MM
"format": str, # Standard, IMAX, 3D, Dolby
"price": float
}
Development 👨💻
Adding New Movies
Edit data/movies.json to add new movies:
{
"movie_id": "mv011",
"title": "New Movie Title",
"rating": "PG-13",
"duration": 120,
"genre": "Action",
"description": "Description of the movie...",
"poster_url": "https://example.com/poster.jpg"
}
Adding New Theaters
Edit data/theaters.json:
{
"theater_id": "th011",
"name": "AMC New Location 15",
"address": "123 Main Street",
"city": "New City",
"state": "NY",
"zip_code": "12345"
}
Adding Showtimes
Edit data/showtimes.json and data/seats.json to add new showtimes and corresponding seat maps.
Testing
Manual Testing
You can test individual tools using the MCP inspector or by connecting to any MCP-compatible client.
Testing with Claude Desktop
- Configure Claude Desktop to connect to your MCP server
- Use natural language to test the booking flow
- Example: "Find me a sci-fi movie showing tonight in Boston"
Configuration ⚙️
Environment Variables
PYTHONPATH: Set to/app/srcfor proper module resolutionPYTHONUNBUFFERED: Set to1for real-time loggingMCP_LOG_LEVEL: Set logging level (DEBUG, INFO, WARNING, ERROR)
Docker Configuration
The server runs in a lightweight Python 3.11 container with:
- Non-root user for security
- Health checks for monitoring
- Volume mounts for data persistence
- Network isolation
Security Considerations 🔒
This is a mock implementation for demonstration purposes. In production:
- Payment Processing: Integrate with real payment gateways (Stripe, PayPal)
- Authentication: Add user authentication and authorization
- Data Validation: Implement comprehensive input validation
- Rate Limiting: Add API rate limiting
- Encryption: Use HTTPS and encrypt sensitive data
- Database: Replace JSON files with a real database
- Logging: Implement structured logging and monitoring
Future Enhancements 🔮
- Real AMC API Integration: Connect to actual AMC Theatres API
- User Accounts: Persistent user profiles and booking history
- Group Bookings: Support for multiple users booking together
- Loyalty Programs: AMC Stubs integration
- Mobile Tickets: Generate QR codes for mobile entry
- Seat Recommendations: AI-powered optimal seat suggestions
- Price Alerts: Notify users of discounts and promotions
- Social Features: Share movie plans with friends
- Accessibility: ADA-compliant seat selection
- Multi-language: International language support
Contributing 🤝
- Fork the repository
- Create a feature branch:
git checkout -b feature/new-feature - Make your changes and add tests
- Commit your changes:
git commit -am 'Add new feature' - Push to the branch:
git push origin feature/new-feature - Submit a pull request
License 📄
This project is licensed under the MIT License - see the LICENSE file for details.
Support 💬
For questions, issues, or feature requests:
- Create an issue in the GitHub repository
- Check the documentation for common solutions
- Review the example conversation flows
Happy movie booking! 🍿🎬
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