A photo of your paper menu, your Instagram handle, or an export from your POS — hand any of them to your AI assistant. Five minutes later: a bilingual QR menu with calories and allergens. No typing, no designer.
Connect Claude, ChatGPT or Cursor in one click, then send it a photo of your paper menu, a PDF or your Instagram handle: "Import this in Arabic and English." It extracts, translates, estimates calories and tags allergens — you approve.
ConnectCSV or JSON from your POS or a competitor export. Mapped and validated, nothing guessed.
UploadSend us your menu or handle. Live in a day, reviewed by a person, with a printed QR stand if you want one.
Book setupAgent estimates are flagged until you confirm. Mandatory since 2019; an afterthought in Western tools.
Diners exclude gluten or nuts and get safe / unsafe / unknown per item — from your attested data, never a guess.
Real right-to-left layout, Arabic-Indic numerals, curated Arabic + Latin font pairs. Translated at import.
Inclusive pricing, running totals, WhatsApp pickup orders. Payments only when you ask for them.
Each venue ships a read-only MCP endpoint, an llms.txt and schema.org markup. "What can I eat here without dairy?" gets answered from your data — by the diner's own assistant.
Read the agent docs$ curl https://sufra.qaema.app/mcp → tools: get_venue_info, get_menu, search_items, check_allergens, find_items find_items({ exclude_allergens: ["milk"], max_calories: 600 }) { "items": [ { "name": "Fattoush", "price": 24, "calories": 180, "safe": true }, { "name": "Lentil soup", "price": 18, "calories": 220, "safe": true }, { "name": "Chicken kabsa", "price": 42, "calories": 780, "safe": true } ], "disclaimer": "Allergen data attested by the venue. Please confirm with staff." }