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Xemoro

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🍔 Scraping UberEats Restaurant Data with a High-Performance API (Menus, Prices, Ratings & More)

#ubereats #webdev #saas #api

Building food delivery tools, price comparison apps, or market research dashboards often requires reliable, real-time restaurant data. Unfortunately, UberEats doesn’t provide a public API for detailed restaurant information.

That’s exactly why I built the UberEats Restaurant Data Scraper API — a fast, structured, and developer-friendly solution for extracting restaurant data from UberEats.com.

👉 API link:
https://rapidapi.com/choukifahd/api/ubereats-restaurant-data-scraper-api

🚀 What Is the UberEats Scraper API?

The UberEats Scraper API provides programmatic access to restaurant data from UberEats using Playwright + Firefox automation under the hood.

It allows you to:

  • Extract full restaurant profiles
  • Get menus with prices & descriptions
  • Retrieve ratings, delivery fees, and estimates
  • Scrape search results or raw HTML
  • Extract custom data using CSS selectors

All responses are returned as structured JSON, ready to be used in any application.

✨ Key Features

  • ⚡ High-performance scraping (optimized for speed)
  • 🔒 Optional proxy support (HTTP / HTTPS / SOCKS5)
  • 📊 Clean, structured JSON responses
  • 🎯 Multiple scraping modes
  • 💰 Menu items with pricing & descriptions
  • ⭐ Ratings, reviews & delivery info
  • 🌍 Geo-targeting with proxies

🔧 Common Use Cases

This API is ideal for:

  • 🍕 Food delivery aggregators
  • 💵 Price comparison platforms
  • 📋 Menu analysis & research
  • 🔎 Restaurant discovery apps
  • 📊 Market research & analytics
  • 🕵️ Competitor monitoring tools

📦 Response Format

Every response includes a statusCode inside the body for consistency.

✅ Success Response 

{
  "statusCode": 200,
  "success": true,
  "data": { }
}
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❌ Error Response 

{
  "statusCode": 400,
  "success": false,
  "error": {
    "message": "Error description",
    "code": "ERROR_CODE"
  }
}
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🏪 Endpoint 1: Scrape UberEats Restaurant Store

POST /ubereats/store

Extract complete restaurant data including:

  • Name & image
  • Ratings & reviews
  • Categories & pricing range
  • Full menu with prices
  • Address & delivery details

Request Body 

{
  "url": "https://www.ubereats.com/store/restaurant-name/store-id",
  "proxy": {
    "server": "http://proxy.example.com:8080",
    "username": "optional_username",
    "password": "optional_password"
  }
}
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Example Response 

{
  "statusCode": 200,
  "success": true,
  "data": {
    "name": "Chipotle Mexican Grill",
    "rating": 4.5,
    "reviewCount": 500,
    "priceRange": "$$",
    "categories": ["Mexican", "Fast Food"],
    "menu": [
      {
        "name": "Burrito Bowl",
        "price": 10.95,
        "currency": "USD"
      }
    ],
    "deliveryTime": "25-35 min",
    "deliveryFee": "$2.99"
  }
}
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cURL Example 

curl -X POST https://ubereats-scraper.p.rapidapi.com/ubereats/store \
  -H "X-RapidAPI-Key: YOUR_API_KEY" \
  -H "X-RapidAPI-Host: ubereats-scraper.p.rapidapi.com" \
  -H "Content-Type: application/json" \
  -d '{
    "url": "https://www.ubereats.com/store/chipotle-mexican-grill-281-broadway/o4NWt86HS_6FL4k__GtaVQ"
  }'
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🌐 Endpoint 2: Fetch Raw HTML

POST /scrape/html

Perfect if you want full control and plan to parse data yourself.

Request Body 

{
  "url": "https://www.ubereats.com/...",
  "waitTime": 2000
}
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Response 

{
  "statusCode": 200,
  "success": true,
  "data": {
    "html": "<html>...</html>",
    "contentLength": 123456
  }
}
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🎯 Endpoint 3: Extract Custom Data with CSS Selectors

POST /scrape/extract

This endpoint lets you define exactly what data you want using CSS selectors.

Request Body 

{
  "url": "https://www.ubereats.com/...",
  "selectors": {
    "restaurantName": {
      "selector": "h1",
      "multiple": false
    },
    "menuItems": {
      "selector": ".menu-item h3",
      "multiple": true
    }
  }
}
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Response 

{
  "statusCode": 200,
  "success": true,
  "data": {
    "restaurantName": "Chipotle Mexican Grill",
    "menuItems": ["Burrito Bowl", "Burrito", "Tacos"]
  }
}
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🔐 Proxy Support (Optional)

All endpoints support proxies for:

  • 🌍 Geographic targeting
  • 🔄 IP rotation
  • 🚫 Avoiding rate limits
  • 🔓 Bypassing restrictions

Supported Protocols

  • http://
  • https://
  • socks5://

Proxy with Authentication 

{
  "proxy": {
    "server": "http://proxy.example.com:8080",
    "username": "myuser",
    "password": "mypass"
  }
}
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🧠 Final Thoughts

If you’re building anything that relies on real UberEats restaurant data, this API saves you weeks of reverse-engineering, browser automation, and infrastructure headaches.

It’s fast, flexible, and built with developers in mind.

👉 Try the UberEats Restaurant Data Scraper API:
https://rapidapi.com/choukifahd/api/ubereats-restaurant-data-scraper-api

If you have feature requests or need custom scraping logic, feel free to reach out. Happy building! 🚀

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