Order_Food_MCP
Click on "Install 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., "@Order_Food_MCPShow me the full menu"
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.
Design principle: business logic (menu.py) is kept fully independent of MCP wiring (server.py), so it can be tested in milliseconds without a running server or LLM.
Menu Design
8 items, each with a unique id, name, and price (float, for now):
ID | Name | Price |
p1 | Margherita Pizza | 299 |
p2 | Pepperoni Pizza | 349 |
b1 | Veggie Burger | 99 |
b2 | Chicken Burger | 129 |
p3 | Farmhouse Pizza | 349 |
dr1 | Cold Coffee | 69 |
dr2 | Mango Shake | 79 |
Related MCP server: MCPizza - Enhanced
Testing Strategy
Tests in test_menu.py cover:
Menu size is within the 5–10 item range
Every item has valid id/name/price
All IDs are unique
Lookup by valid ID returns the correct item
Lookup by invalid ID returns
None(not an exception)
Run with:
uv run pytest test_menu.py -vStatus
[done] Week 1: MCP fundamentals, hello-world server, local LLM verified
[done] Week 2: Menu data model, mock data, lookup function, tests passing
[done] Week 3: get_menu MCP tool, tests, live LLM demo (Claude Desktop)
Week 4: Order logic (pricing, validation)
Week 3 Demo
Verified get_menu_tool end-to-end in Claude Desktop: asked "What food can I order?"
in natural language (no explicit tool mention), and the LLM correctly called
get_menu_tool and returned the full 8-item menu in chat.
Also verified via MCP Inspector: tool discoverable, returns valid JSON with ( cmd - npx @modelcontextprotocol/inspector uv run server.py ) id/name/price for all 8 items.
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