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🍔 UberEats Menu Scraper + Analytics

Extract complete, structured menu data from any UberEats store — including item names, prices, sections, descriptions, and images. Just paste the store URLs directly from your browser. No UUIDs, no API keys, no setup required.

Built for price monitoring, competitive restaurant analysis, food-tech applications, and AI-powered food discovery.

💰 Transparent, usage-based pricing

$6.90 per 1,000 menu items — you only pay for what you extract.

Higher Apify subscription tiers (Bronze, Silver, Gold) automatically receive discounted rates. No hidden fees, no per-run charges beyond the standard Actor start cost.

✨ What does this Actor do?

• Accepts one or more UberEats store page URLs copied directly from your browser.
• Automatically decodes the store identifier from the URL — works for both US and international stores.
• Fetches all stores concurrently with a built-in retry mechanism for maximum reliability.
• Extracts every menu item across all sections and subsections.
• Computes per-store analytics (price coverage, image coverage, min/max/avg price, promotion detection).
• Outputs structured data across three separate datasets ready for JSON, CSV, or Excel export.
• Enforces limits for free Apify accounts automatically.

📝 Input

Supported URL formats

Both US and international UberEats URLs are supported:

# US — UUID is visible directly in the URL
https://www.ubereats.com/store/mcdonalds-fillmore/209c6d0b-8bf5-579c-926b-436bd3bf839c
# International
https://www.ubereats.com/cl/store/arma-tu-hamburguesa-arica/reNyJaIAXPiMDQ7hjscVHA

Example input

{
"store_urls":[
"https://www.ubereats.com/store/mcdonalds-fillmore/209c6d0b-8bf5-579c-926b-436bd3bf839c",
"https://www.ubereats.com/cl/store/arma-tu-hamburguesa-arica/reNyJaIAXPiMDQ7hjscVHA"
]
}

How to find a store URL

Navigate to any restaurant on ubereats.com and copy the URL from your browser's address bar. That's it.

📦 Output

This Actor produces three separate datasets per run, each accessible from the Storage tab in the Apify run detail.

1. Default dataset — Menu Items

One record per menu item. This is the main output.

{
"subsection_id":"2c05b603-56ea-5441-97f9-019f8a7ebc2f",
"subsection_name":"Most Popular",
"store_id":"ad2a8786-4e0e-45f4-a79f-a1dfb38d797f",
"section_id":"c65630da-f63f-5258-8f7d-f94f2bbba0cb",
"section_name":"Lunch",
"country_code":"us",
"region_code":"dc",
"data_file":"ad2a8786-4e0e-45f4-a79f-a1dfb38d797f",
"has_customizations":true,
"is_sold_out":false,
"is_available":true,
"menu_item_id":"a34b9dd7-c831-5b77-bfd4-56ffa252feab",
"menu_item_name":"Medium French Fries",
"menu_item_price":499,
"menu_item_price_promotion":null,
"menu_item_price_tagline":{
"text":"$4.99 • 320 Cal.",
"textFormat":"<span>$4.99<span style=\"color:#757575\"> • 320 Cal.</span></span>",
"accessibilityText":"$4.99, 320 Cal."
},
"menu_item_description":null,
"menu_item_image":"https://tb-static.uber.com/prod/image-proc/processed_images/c821c5db2718d95dd1fd68002987ec27/c67fc65e9b4e16a553eb7574fba090f1.jpeg",
"store_url":"https://www.ubereats.com/store/mcdonalds-bwr-rbd-80017-ny-aves/ad2a8786-4e0e-45f4-a79f-a1dfb38d797f",
"extraction_date":"2026-03-25",
"extraction_datetime":"2026-03-25T06:20:40.673495+00:00",
"main_task_id":"4e8b5aba-a061-4350-8852-32f114f8eabe",
"main_task_started":"2026-03-25T06:20:38.745046+00:00",
"position":0
}

2. store-analytics dataset — Per-store Summary

One record per scraped store. Useful for competitive benchmarking, data quality audits, and price intelligence dashboards.

{
"store_id":"ade37225-a200-5cf8-8c0d-0ee18ec7151c",
"country_code":"cl",
"total_sections":4,
"total_subsections":12,
"total_items":38,
"price_coverage_pct":100.0,
"image_coverage_pct":94.74,
"min_price":150000,
"max_price":650000,
"avg_price":312500.0,
"has_promotions":false,
"extraction_date":"2026-03-25",
"extraction_datetime":"2026-03-25T04:30:35.319213+00:00",
"main_task_id":"36a31035-82ad-41a0-8b24-37ade70e2c44",
"main_task_started":"2026-03-25T04:30:31.438177+00:00"
}

3. run-summary dataset — Run-level Report

One record per Actor run. Ideal for monitoring scheduled runs, auditing failures, and tracking extraction history.

{
"main_task_id":"36a31035-82ad-41a0-8b24-37ade70e2c44",
"main_task_started":"2026-03-25T04:30:31.438177+00:00",
"main_task_finished":"2026-03-25T04:31:10.000000+00:00",
"country_code":"cl",
"stores_requested":5,
"stores_succeeded":4,
"stores_failed":1,
"failed_store_ids":["ade37225-a200-5cf8-8c0d-0ee18ec7151c"],
"total_menu_items":142,
"free_user":false
}

💎 Free vs Paid

Free account limits

When running with a free Apify account, the following restrictions apply automatically:

• Only the first store URL is processed.
• A maximum of 5 menu items is returned.

Upgrade to a paid Apify plan to unlock bulk scraping, full analytics, and multi-country support.

🚀 How to run

Apify Console

1. Click Try for free on this page.
2. Paste your UberEats store URLs into the store_urls field.
3. Click Start and wait for the run to complete.
4. Download results from the Storage tab in JSON, CSV, or Excel format.

Apify API

curl-X POST \
"https://api.apify.com/v2/acts/datacach~ubereats-menu-scraper/runs?token=YOUR_TOKEN"\
-H"Content-Type: application/json"\
-d'{
 "store_urls": [
 "https://www.ubereats.com/store/mcdonalds-fillmore/209c6d0b-8bf5-579c-926b-436bd3bf839c"
 ]
 }'

Schedule recurring runs

Use Apify's built-in Scheduler to monitor menus on a daily or weekly basis and detect price changes over time.

🛠 Technical notes

• Built with Python 3 and the Apify SDK.
• Concurrent store fetching via asyncio with a semaphore (up to 32 workers by default).
• Automatic retry — stores that fail on the first attempt are retried once with a fresh authentication token before being marked as permanently failed.
• URL decoding — international UberEats URLs encode the store ID as a URL-safe base64 hash; the Actor decodes it automatically.
• Duplicate URLs in the input are deduplicated while preserving order.
• Supports UberEats menu API formats v1 (catalogSectionsMap) and v2 (sectionEntitiesMap).
• All timestamps are in UTC.

🔗 Related Actors

💬 Support

Need help or have a feature request? Reach us via the Apify inbox on our profile page.

✨ Credits

Developed and maintained by the DataCach team.

This Actor is neither affiliated with, sponsored by, nor endorsed by Uber Eats or Uber Technologies Inc. Use responsibly and in accordance with the Apify Terms of Service and Uber Eats' own terms of use.