MCPizza - Enhanced
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@MCPizza - Enhanced Find the best coupons for a large pepperoni pizza near 90210."
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
š MCPizza - Enhanced
An educational MCP (Model Context Protocol) server demonstrating AI-powered pizza ordering with Domino's API integration.
ā ļø Important: This project is for educational purposes only. While it integrates with Domino's real API, actual order placement is blocked by CAPTCHA requirements. See Limitations for details.
Credits
This project is based on GrahamMcBain/mcpizza, with significant enhancements:
Original Project
Author: Graham McBain
Purpose: Educational MCP protocol demonstration
Design: Safe-mode ordering without real placement
Our Enhancements
ā Real API Integration - Actually calls Domino's pricing and validation APIs
ā Pizza Customization -
add_pizza_with_toppingstool for proper coupon + topping configurationā Interaction Logging - Complete 2-way logging system for all MCP interactions
ā Coupon Discovery -
get_couponsandget_ordering_guidancetoolsā Enhanced Error Handling - Detailed error reporting and validation
ā Comprehensive Documentation - WORKFLOW.md with step-by-step instructions
Related MCP server: Food402
What This Project Demonstrates
MCP Protocol Integration - Full implementation of Model Context Protocol
Real-world API Interaction - Integration with Domino's unofficial API
Complex Tool Orchestration - 12 tools working together for multi-step workflows
State Management - Order state management across tool calls
Error Handling - Graceful handling of API validation and errors
Features
Store & Menu Tools
š
find_stores- Find nearby Domino's by address or zipšŖ
get_store_info- Detailed store information and hoursš
get_menu- Complete menu with categoriesš
search_menu- Search for specific itemsš
get_coupons- Discover available deals and coupons
Ordering Tools
š
create_order- Initialize a new orderš
add_pizza_with_toppings- Add customized pizzas with toppings (NEW!)ā
add_item_to_order- Add any menu itemšļø
view_order- Preview order details and pricingšļø
clear_order- Clear current orderš³
place_order- Attempt to place order (blocked by CAPTCHA)
Guidance Tools
šÆ
get_ordering_guidance- AI-powered deal recommendations (NEW!)
Installation
Prerequisites
Python 3.10+
uv package manager
Setup
# Clone the repository
git clone https://github.com/dshanklin-bv/mcp-pizza.git
cd mcp-pizza
# Install dependencies
uv pip install -e .Claude Desktop Integration
Add to ~/Library/Application Support/Claude/claude_desktop_config.json:
{
"mcpServers": {
"pizza": {
"command": "uv",
"args": [
"--directory",
"/path/to/mcp-pizza",
"run",
"mcpizza"
]
}
}
}Usage
See WORKFLOW.md for complete ordering workflow documentation.
Basic Example
1. Find stores: "find pizza stores near 76104"
2. Get coupons: "what deals are available at store 8022?"
3. Get guidance: "I want a deep dish sausage and pepperoni pizza"
4. Create order: Create order with your details
5. Add pizza: Use add_pizza_with_toppings with coupon code
6. View order: Review pricing and details
7. (Optional) Place order: Will be blocked by CAPTCHAArchitecture
The codebase follows a clean, modular architecture with separation of concerns:
mcp-pizza/
āāā mcpizza/
ā āāā server.py # Main MCP server (303 lines, down from 1308!)
ā āāā logger.py # Interaction logging system
ā āāā __main__.py # Entry point
ā ā
ā āāā models/ # Pydantic parameter models
ā ā āāā params.py # Tool parameter definitions
ā ā
ā āāā services/ # Business logic layer
ā ā āāā store_service.py # Store lookup & menu browsing
ā ā āāā order_service.py # Order creation & management
ā ā āāā payment_service.py # Payment processing
ā ā āāā guidance_service.py # AI ordering guidance
ā ā
ā āāā tools/ # MCP tool handlers
ā ā āāā store_tools.py # Store-related tools
ā ā āāā menu_tools.py # Menu-related tools
ā ā āāā order_tools.py # Order-related tools
ā ā āāā guidance_tools.py # Guidance tools
ā ā
ā āāā api/ # Domino's API client
ā ā āāā endpoints.py # API endpoint constants
ā ā āāā client.py # HTTP client wrapper
ā ā
ā āāā utils/ # Utilities
ā āāā mock_order.py # Mock order object creation
ā
āāā tests/ # Comprehensive test suite (18 tests)
ā āāā test_models.py # Model validation tests
ā āāā test_utils.py # Utility function tests
ā āāā test_api_client.py # API client tests
ā āāā test_services.py # Service layer tests
ā
āāā examples/ # Example scripts
ā āāā test_mcp_with_ollama.py # Autonomous testing
ā
āāā logs/ # Interaction logs (gitignored)
āāā WORKFLOW.md # Complete workflow documentation
āāā README.md # This fileBenefits of This Architecture
Maintainability: Each module has a single responsibility
Testability: Services and utilities are easily unit tested
Readability: Clear separation between MCP layer, business logic, and API calls
Scalability: Easy to add new tools or services
Reusability: Services can be reused outside of MCP context
Logging
All MCP interactions are automatically logged to logs/interactions_YYYYMMDD.log:
Tool calls with full arguments
Tool responses with previews
State changes (order creation, items added)
Errors with context
Log format is JSON for easy parsing and analysis.
Limitations
CAPTCHA Requirement
Domino's API requires CAPTCHA verification for order placement. Our system successfully:
ā Validates pizza configurations
ā Prices orders correctly (e.g., $11.90 for medium 2-topping)
ā Accepts payment structure
ā Cannot submit final order (blocked by
recaptchaVerificationRequired)
This is an intentional fraud prevention measure by Domino's and cannot be bypassed without violating their terms of service.
What Works
Store lookup and menu browsing
Coupon discovery and deal analysis
Order validation and pricing
Complete order preparation
All MCP protocol features
What Doesn't Work
Final order submission (CAPTCHA required)
Real payment processing
Development
Testing
# Run autonomous test suite (tests all tools except order placement)
python test_mcp_with_ollama.pyContributing
This is an educational project demonstrating MCP protocol integration. Contributions that enhance the educational value are welcome!
Technical Details
MCP SDK: Official Model Context Protocol SDK
API Library: pizzapi (unofficial Domino's API wrapper)
Order Structure: Mock order object with real API calls
Validation: Multi-step validation (structure ā pricing ā placement)
Disclaimer
ā ļø Educational Use Only
This project is for learning about:
Model Context Protocol implementation
Real-world API integration
Multi-tool orchestration
State management in AI assistants
Do not use for actual pizza ordering. Use Domino's official website or mobile app instead.
License
MIT License
Based on GrahamMcBain/mcpizza (MIT License)
Acknowledgments
Graham McBain - Original mcpizza project and MCP implementation
pizzapi contributors - Unofficial Domino's API wrapper
Anthropic - Model Context Protocol specification
Built with Claude Code š¤
Available Tools
12 toolsadd_item_to_orderB
Add a menu item to the current order. Must create an order first.
Inputs: item_code (required), quantity, options.
add_pizza_with_toppingsC
Add a customized pizza with toppings using a coupon code. Handles proper product + topping configuration.
Inputs: coupon_code (required), toppings (required), size, crust.
clear_orderB
Clear the current order and start over.
Inputs: no named parameters.
create_orderB
Create a new order for delivery or carryout. Required before adding items.
Inputs: store_id (required), customer_name (required), customer_email (required), customer_phone (required), +5 more.
find_storesB
Find nearby Domino's stores by address or zip code. Returns store IDs, addresses, and phone numbers.
Inputs: query (required).
get_couponsC
Get available coupons and deals for a store. Returns coupon codes, descriptions, and prices.
Inputs: store_id (required).
get_ordering_guidanceC
Get AI guidance on how to build the best order based on user preferences. Analyzes deals, suggests optimal pizza counts, and provides ordering strategy.
Inputs: store_id (required), user_request (required).
get_store_infoC
Get detailed information about a specific Domino's store including hours and services.
Inputs: store_id (required).
place_orderA
ā ļø PLACES A REAL ORDER with real payment! Submit the current order to Domino's. Requires payment information.
Inputs: card_number (required), card_expiry (required), card_cvv (required), card_zip (required).
view_orderB
View the current order including all items, prices, and totals.
Inputs: no named parameters.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
Loading tool schema changelogā¦
TDQS
Scored across 12 tools
Each tool has a clearly distinct purpose with no significant overlap. For example, 'get_menu' retrieves the full menu, while 'search_menu' filters it, and 'add_item_to_order' and 'add_pizza_with_toppings' handle different item types. The descriptions clearly differentiate their functions, making misselection unlikely.
All tool names follow a consistent verb_noun pattern using snake_case, such as 'create_order', 'get_menu', and 'place_order'. This uniformity makes the tool set predictable and easy to understand, with no deviations in naming style.
With 12 tools, the server is well-scoped for a pizza ordering domain. Each tool serves a specific role in the ordering workflow, from store lookup to order placement, without being excessive or insufficient for the intended functionality.
The tool set provides complete coverage for the pizza ordering domain, including store discovery, menu browsing, order creation and management, coupon retrieval, and final placement. There are no obvious gaps, as all essential CRUD and lifecycle operations are covered, ensuring agents can handle the full process without dead ends.
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