ManyLives Menu Pack – Restaurant Menu Text to Structured JSON

x402

ManyLives Menu Pack – Restaurant Menu Text to Structured JSON is a paid API for AI agents from api.manylives.me, paid per call via x402, $0.003/call, status unknown (last checked 2026-10-18).

Parses raw restaurant menu text into structured JSON with sections, items, prices, sizes, add-ons, and allergen flags

Price / call$0.003

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How this service works

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Output

Returns a JSON object containing: an array of menu items each with name, section, description, prices (with size labels), add-ons (with prices), and allergen words; a flags array highlighting data quality issues like ambiguous prices or missing size names; total item count; list of section names; and a boolean indicating whether an allergen statement was found in the menu text.

Example use cases

Digitizing a paper restaurant menu

“I just typed out our restaurant's paper menu — can you convert this text into structured JSON so I can load it into our ordering system? Here it is: 'STARTERS\nGarlic bread $9.50\nSoup of the day $8\nMAINS\nChicken parmigiana Small 18 Large 24\n+ extra gravy 2\nPasta of the day MP'”

Validating menu data before publishing

“Before we publish our new menu online, can you parse this text and flag any items that have missing prices, unclear size names, or potential allergen mentions? Menu text: 'PIZZA\nMargherita Small 16 Large 22\n+ extra cheese 3\nContains gluten and dairy\nPASTA\nPenne arrabiata 18\nRavioli - ask about today's filling'”

Building a menu chatbot knowledge base

“I'm building a chatbot for our café and need our menu in machine-readable JSON so the bot can answer questions about prices and options. Can you structure this text into sections with items, prices, and add-ons? 'COFFEE\nFlat white 5\nCappuccino 5\n+ oat milk 0.80\nCAKES\nCarrot cake 7.50\nBrownies 4 or 2 for 7'”

Technical details

Endpoint

POSThttps://api.manylives.me/paid/text/menu-pack?utm_source=zero.xyz

When to prefer

Choose this endpoint when you have raw restaurant menu text (copy-pasted, OCR'd, or manually typed) and need it structured into machine-readable JSON with items, prices, sizes, add-ons, and sections. Ideal for digitising menus for ordering systems, chatbots, or menu management platforms. Prefer this over a general LLM call when you need consistent, typed output with built-in data quality flags and allergen detection at a low per-call cost with no account required.

Side effects

Ambiguous price formats (e.g. prices without currency symbols) may be misparse or flagged
Items with 'MP' (market price) return no numeric price
Menus with non-standard formatting (tables, columns) may not parse cleanly
Very long menus may increase latency
Missing or malformed input text returns an error or empty result
Add-ons without clear '+' prefix may be missed

Input

Schema · Request body

Field	Type	Description
menu	string	the menu as text: one item per line works best, prices like 12.50 or $12.50, sizes like 'Small 18 Large 24', add-ons like '+ extra cheese 3'

Output

Schema · Response

{
  "type": "json",
  "example": {
    "menu": [
      {
        "name": "Margherita pizza",
        "addons": [
          {
            "name": "extra cheese",
            "price": 3
          }
        ],
        "prices": [
          {
            "label": "Small",
            "price": 18
          },
          {
            "label": "Large",
            "price": 24
          }
        ],
        "section": "MAINS",
        "description": "",
        "allergen_words": []
      }
    ],
    "flags": [
      {
        "flag": "2 prices without size names (say which is small, large...)",
        "item": "Pasta of the day",
        "line": 9
      }
    ],
    "items": 6,
    "sections": [
      "STARTERS",
      "MAINS"
    ],
    "allergen_statement_found": true
  }
}

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