Uber Eats Menu Scraper

🍔 Uber Eats Menu Scraper

Extract restaurant menus and store data from Uber Eats at scale. The Uber Eats Menu Scraper pulls full menus with prices and item IDs, plus ratings, addresses, opening hours and contact info from any Uber Eats store page — no browser, no JavaScript rendering required.

✨ Features

• 🏪 Full Store Profile: Name, cuisines, price range, hero images, address, geo coordinates, phone, rating, and review count.
• 📋 Complete Menu: Every menu section with item name, description, price, currency, item UUID, and "#N most liked" popularity tag.
• 🕒 Opening Hours & Delivery: Structured opening-hours specifications and delivery methods (OwnFleet, PickUp).
• 🌍 Global Coverage: Works across all 25+ Uber Eats markets — US (/store/...) and country-prefixed URLs (/tw/, /mx/, /jp/, /fr/, ...).
• 🗺️ Three Discovery Modes: Direct store URLs, city/category seeds (e.g. new-york-city/pizza), or full sitemap shards (~50K URLs each, 26 shards total).
• ⚡ Fast & Lightweight: Pure HTTP + Cheerio, no headless browser — reads server-rendered JSON-LD directly.

🛠️ How It Works

1. Choose your discovery mode – paste Uber Eats /store/... URLs directly, list city/category seeds, or pick sitemap shard indices.
2. Run the Actor – it parses each store's embedded JSON-LD and pushes one structured record per restaurant.
3. Download the data – export the dataset as JSON, CSV, Excel, or HTML.

⚙️ Input

Configure the run from the Input tab in Apify Console or via the API. All fields are optional, but you must supply at least one of storeUrls, categorySeeds, or sitemapShards.

Field	Type	Description	Default
storeUrls	array	Direct Uber Eats store URLs, e.g. https://www.ubereats.com/store/{slug}/{storeId}. Scraped immediately, no discovery step.	[]
sitemapShards	array of integers (0–25)	Sitemap shard indices to crawl for store discovery. Each shard contains ~50K store URLs across all countries.	[]
countryFilter	array of strings	Restrict discovered URLs to these two-letter country codes (e.g. ["US","GB","TW"]). Empty = no filter. US stores have no country prefix; international stores are prefixed with /{cc}/store/.	[]
categorySeeds	array of objects	City/category pairs, e.g. {"city":"new-york-city","category":"pizza"}. Each becomes https://www.ubereats.com/category/{city}/{category} and all /store/... links on the page are enqueued.	[]
maxStores	integer	Maximum number of store detail pages to scrape across all discovery sources. 0 = unlimited.	100
proxyConfiguration	object	Proxy settings. Apify residential proxies recommended for sitemap-scale runs.	{ "useApifyProxy": true }

Example input

{
    "storeUrls": [
        { "url": "https://www.ubereats.com/store/brookiez-77-christopher-st-store/c4BEKnGoSJmcg85J8bFexQ" }
    ],
    "categorySeeds": [
        { "city": "new-york-city", "category": "pizza" }
    ],
    "sitemapShards": [0, 1],
    "countryFilter": ["US"],
    "maxStores": 500
}

📊 Sample Output Data

The scraper outputs one structured JSON record per store, with the full menu nested inside.

[
    {
        "url": "https://www.ubereats.com/store/dominos-4010-n-conway-aves/JGNuF4GSWCC5dHas2xHyqg",
        "storeId": "JGNuF4GSWCC5dHas2xHyqg",
        "name": "Domino's (4010 N CONWAY AVE)",
        "cuisines": ["Pizza"],
        "priceRange": "$",
        "images": ["https://tb-static.uber.com/prod/image-proc/processed_images/..."],
        "address": {
            "street": "4010 N Conway Ave",
            "city": "Mission",
            "region": "TX",
            "postalCode": "78574",
            "country": "US"
        },
        "geo": { "lat": 26.244, "lng": -98.297 },
        "phone": "+16824086498",
        "rating": 4.5,
        "reviewCount": 130,
        "deliveryMethods": ["OwnFleet", "PickUp"],
        "openingHours": [
            { "days": ["Monday", "Tuesday", "Wednesday"], "opens": "10:00", "closes": "23:00" }
        ],
        "menu": [
            {
                "section": "Pizzas",
                "items": [
                    {
                        "itemId": "01e54a0e-dd7e-5bc2-bae1-53c4a91c9aa1",
                        "name": "Pacific Veggie",
                        "description": "Roasted red peppers, onions, mushrooms",
                        "price": 13.09,
                        "currency": "USD",
                        "popularityTag": "#1 most liked"
                    }
                ]
            }
        ]
    }
]

Data is available in JSON, CSV, Excel, and HTML formats from the Apify Console or via the dataset API.

Power up your food-delivery analytics, price tracking, or competitive research with the Uber Eats Menu Scraper today! 🚀