Pricing

from $2.20 / 1,000 results

Try for free

Go to Apify Store

Uber Eats Scraper | Menus Stores Feed Search

Try for free

Scrape Uber Eats restaurants, menus, city/category SEO pages, delivery feed & search across 40+ locales. Extract store UUID, ratings, ETA, price buckets, cuisine slugs. Export Excel/CSV/JSON. Unofficial — not affiliated with Uber.

Pricing

from $2.20 / 1,000 results

Rating

0.0

(0)

Developer

kane liu

Actor stats

Bookmarked

Total users

Monthly active users

4 days ago

Last modified

Uber Eats Scraper — Restaurants, Menus, Feed & Search

Scrape Uber Eats restaurant listings, menus, city/category SEO pages, and delivery feed/search — then download structured food-delivery data as Excel, CSV, or JSON.

Use this Actor as a practical Uber Eats data API for multi-locale restaurant discovery, cuisine research, menu monitoring, and delivery-market tracking. Pick a locale and mode, then get Dataset rows with store UUIDs, titles, ratings, ETA, price buckets, cuisine slugs, and permalinks.

maxResults is the maximum number of Dataset rows delivered and billed for each start URL or the one scalar mode input. The default is 70, and larger values are collected in parts of 70. Store, menu-item, city, category, and cuisine rows share each input's allowance, and the run stops at your maximum total charge. Search store rows keep only matchedItemCount; set includeMatchedItems: true to emit each matched dish as its own itemType: "menu_item" row with the parent store fields copied onto it.

Scrape city SEO pages, cuisine categories, cuisine discovery, location indexes, address-aware feed, global search, store menus, menu-item customizations, and brand store lists
Cover 40+ Uber Eats locales (us, ca, gb, au, fr, jp, mx, br, …); the market follows your store URL, start URLs or a Canadian address when you leave locale empty
Extract store UUID / menuItem UUID, title, URL, rating, price bucket, ETA, formatted address, cuisine / city slugs
Store rows can include the store's public phone number, latitude / longitude, a structured address, review count, cuisine categories, and (search) the matching-dish count. Matching dishes are opt-in separate rows. enrichDetails is off by default because store mode also emits separately billed menu rows; turn it on when you want store-detail enrichment.
Locate deliveries by a human address, an encoded pl, or latitude + longitude (feed / search / resolve_place)
Export to Excel / CSV / JSON, or connect Make, n8n, Zapier, Python, or the Apify API
Pay per event — Actor start + each Dataset result; platform usage is included (you do not pay separate Apify compute on top)

Unofficial tool. This Actor is not affiliated with, endorsed by, or sponsored by Uber Technologies, Inc. or Uber Eats. It collects publicly reachable listing surfaces and does not place orders, checkout, or access private Uber accounts.

What does the Uber Eats Scraper do?

Uber Eats Scraper lets you extract structured restaurant and menu data from ubereats.com without operating your own anti-bot browser fleet. Give it a locale and a mode (for example city, search, or store), then start a run.

Under the hood, the Actor:

Validates your input (mode, locale, city/address/store identifiers, max results)
Enforces free-tier caps when you are on a free Apify plan
Collects public Uber Eats pages and endpoints through a managed backend (no browser)
Parses listing / menu signals into normalized Dataset records
Writes RUN_SUMMARY (and ERROR_SUMMARY on failure) to the key-value store

You run it like any other Apify Actor — schedule it, call it from the API, or plug it into automations.

What Uber Eats data can I extract?

Data	City / category	Feed / search	Store	Menu item	Brand	Resolve place
Store / item UUID	✅	✅	✅	✅	✅*	—
Title / name	✅	✅	✅	✅	✅*	—
URL / slug	✅	✅	✅	✅*	✅*	—
Rating / ETA / price bucket	✅*	✅*	✅*	✅*	✅*	—
Cuisine / city slug	✅	✅*	✅*	—	—	—
Formatted address / pl	—	✅*	✅*	—	—	✅
Structured address / latitude / longitude	✅†	✅	✅	—	✅†	✅
Store phone number	✅*†	✅*	✅*	—	✅*†	—
Matching dishes + prices	—	✅ (search)	—	—	—	—
Menu sections / customizations	—	—	✅*	✅	—	—

*When present on the page or script state. Feed/search prefer address-aware discovery; city/category use SEO listing pages. Phone numbers appear when the store publishes one; placeholder numbers such as 555-0100 are left out.

†With enrichDetails (default off): one extra request per store; in store mode it also emits separately billed menu rows.

Why scrape Uber Eats?

Uber Eats is one of the largest food-delivery marketplaces worldwide. Teams scrape Uber Eats to:

Map restaurant supply by city, cuisine, or brand across countries
Track menus and prices for competitive monitoring
Build delivery-market datasets (ratings, ETA, price buckets)
Discover stores near a delivery address (feed / search with address or pl)
Seed CRM / research workflows with store UUIDs and Uber Eats URLs

Compared with Uber Eats Actors that only cover menu URLs, one country, or reviews-only, this Actor focuses on multi-locale coverage with city SEO, cuisine discovery, address feed/search, store menus, brands, and place resolve in one input form.

More Actors like this

Need restaurant / local / travel data outside Uber Eats, or a different vertical? Use a dedicated Actor below for structured fields. Use this Actor for Uber Eats multi-locale restaurants, menus, feed, and search.

Similar local, maps & travel scrapers

Prefer another specialized scraper?

If your target has a specialized Actor below, use that first — usually cheaper and more structured than a generic scrape.

Jobs & Freelance

Real Estate

E-commerce

Social & Content

Ads Intelligence

General Tools

→ See the full catalog in Related Actors below, or browse apify.com/lentic_clockss.

How to scrape Uber Eats (no code required)

Create a free Apify account
Open Uber Eats Scraper
Choose a mode: city, category, cuisines, location, feed, search, store, menu_item, brand, resolve_place, or startUrls
(Optional) Choose a locale; leave it empty to follow your URL or address (otherwise us)
Enter a citySlug, cuisineSlug, query + address/pl, storeUrl / storeUuid, or startUrls
(Optional) Set maxResults, maxPages, includeCuisines, enrichDetails
Click Start and download the Dataset as JSON, CSV, Excel, or JSONL

Start with maxResults: 5–10 to verify the query, then scale up.

How much does it cost to scrape Uber Eats?

This Actor uses pay-per-event pricing. You are charged for:

Event	Price
Actor Start (`apify-actor-start`)	$0.005 per start
Result (`apify-default-dataset-item`)	$3.00 / 1,000 results ($0.003 each on FREE/BRONZE)

Platform usage costs are included — you do not pay separate Apify compute/proxy usage for this Actor on top of the event prices above (User pays platform usage costs = No).

Store tier pricing (results)

Tier	$/1,000	per result
FREE*	$3.00	$0.003
BRONZE	$3.00	$0.003
SILVER	$2.60	$0.0026
GOLD	$2.20	$0.0022
PLATINUM	$2.00	$0.002
DIAMOND	$1.60	$0.0016

*Store tier discounts apply to paying Apify customers on higher tiers.

Example cost estimates

Results collected	Approx. event cost*
100	~$0.31
1,000	~$3.01
10,000	~$30.01

*Assumes one Actor start at default memory billing for start events, plus $0.003 per Dataset item on FREE/BRONZE. Exact start billing can scale with allocated memory (one start event per GB, minimum one).

Free Apify trial credit can cover a small test run — try maxResults: 5 first.

Free Apify plan limits (Actor-enforced)

Cap	Free Apify plan	Paying
Runs of this Actor	10 total	Unlimited
Rows per run	200	Schema max (500)

Limits are set by the Actor developer, not Apify. Quota hits return SUCCEEDED with RUN_SUMMARY.status=FREE_TIER_LIMIT.

Input examples

City SEO listings (US)

{
  "mode": "city",
  "locale": "us",
  "citySlug": "denver-co",
  "maxResults": 20
}

Cuisine category (Canada)

{
  "mode": "category",
  "locale": "ca",
  "citySlug": "vancouver-bc",
  "cuisineSlug": "thai",
  "maxResults": 15
}

Delivery search by address

{
  "mode": "search",
  "locale": "us",
  "query": "pizza",
  "address": "1600 Broadway, Denver, CO",
  "maxResults": 10
}

Delivery feed by coordinates

{
  "mode": "feed",
  "locale": "gb",
  "latitude": "51.5074",
  "longitude": "-0.1278",
  "maxResults": 50
}

{
  "mode": "store",
  "locale": "us",
  "storeUrl": "https://www.ubereats.com/store/example-slug/AbCdEfGh",
  "maxResults": 50
}

Resolve delivery place (`pl`)

{
  "mode": "resolve_place",
  "locale": "us",
  "address": "701 S Miami Ave, Miami, FL"
}

Output

Each Dataset item is a normalized Uber Eats row. Common fields:

Field	Description
`itemType`	`store`, `menu_item`, `city`, `cuisine`, …
`uuid` / `storeUuid` / `menuItemUuid`	Stable identifiers when available
`title` / `name`	Display name
`url`	Uber Eats permalink
`locale` / `citySlug` / `slug`	Locale and SEO slugs
`ratingValue` / `reviewCount` / `reviewCountText` / `etaText` / `priceBucket`	Listing signals when present (`reviewCount` is a number; `reviewCountText` keeps what Uber Eats shows, e.g. `5000+`)
`formattedAddress` / `streetAddress` / `city` / `region` / `postalCode` / `country` / `address`	Address text and its parts, checked against official postal and street-address data (see below)
`addressCorrections`	Present when a postal code, city or region was filled in or corrected: `field`, `from`, `to`, `source`, `reason`
`addressCheck`	How the delivered address compares with the reference data: `status` (`ok` / `conflict` / `unverifiable` / `unavailable`), `precision`, `conflicts`
`phoneNumber` / `phones`	Store's public phone number, when published
`latitude` / `longitude` / `geo`	Store coordinates
`categories` / `isOrderable` / `currencyCode`	Cuisine tags, open-for-orders flag, market currency
`rank` / `searchQuery` / `matchedItems`	Position in results; for search, the query and up to five matching dishes with prices
`scrapedAt`	ISO timestamp

Address corrections are conservative. A missing postal code, city or region is filled in. A partial postal code (EC4N 6, M5V) is completed with the code of the same house. A postal code is replaced only when the reference has the very same house (same number and street, within 300 m of the store's map pin) in another code. A postal code that both the map pin and the city put far away is removed, and refilled when the reference knows the right one. Coordinates and street names are never changed.

Run artifacts in the default key-value store:

INPUT_ECHO — sanitized input (no secrets / no internal endpoint URLs)
RUN_SUMMARY — status, counts, warnings, free-tier flags
ERROR_SUMMARY — present only on hard failures

Tips for best results

Prefer short verification runs (maxResults: 5) before large jobs
Leave locale empty and the run uses the country of your address (London → gb, Toronto → ca); set it yourself when you search by latitude + longitude or pl outside the US
Prefer address or latitude + longitude over hand-crafted pl unless you already have a valid encoded place
Search returns up to 80 stores per page; set maxResults above 80 to page deeper
Uber Eats shows one page per city or category; city mode tops up from the delivery feed at the city centre when you ask for more
Use SEO city/category modes when you do not need a delivery pin; use feed/search when results must match an address

FAQ

Is this an official Uber Eats API?

No. It is an unofficial scraper for publicly reachable Uber Eats pages. Not affiliated with Uber.

Do I need my own proxies?

No. The Actor's backend handles network access. There is no proxy setting in the input.

Can I scrape menus?

Yes — use mode=store with storeUrl or storeUuid, or mode=menu_item with menuItemUuid (+ store context when required).

Does platform usage cost extra?

No. With this Actor’s pay-per-event setup, users do not pay separate Apify platform usage on top of Actor Start + result events.

Legal & ethical use

Use this Actor only for legitimate purposes and in compliance with applicable laws and Uber’s terms. Do not scrape personal data you are not entitled to process. Respect rate limits and do not use the data to harm restaurants, drivers, or diners.

Support

Questions or feature requests? Open an issue on the Actor page or contact the developer via Apify Console.

Keywords: Uber Eats scraper, UberEats API, Uber Eats restaurant scraper, Uber Eats menu scraper, Uber Eats feed scraper, Uber Eats search scraper, food delivery data, store UUID, cuisine slug, multi-locale Uber Eats, pay per event

All 77 public Actors from [lentic_clockss]. Click a name to open the Store detail page.

Jobs & Freelance

Real Estate

E-commerce

Travel & Stays

Ads Intelligence

Local & Maps

Google Maps Scraper

General Tools

→ Browse the full profile: apify.com/lentic_clockss

🍴Uber Eats Scraper [PPR]

borderline/uber-eats-scraper-ppr

Pay per result - Fast and cost-effective Uber Eats Scraper requiring just a search query and location or using stores urls. Instantly retrieve comprehensive restaurant data, including names, phone, ratings, locations, and menus. Seamlessly integrates, offering a highly efficient data solution.

borderline

666

5.0

(3)

Uber Eats Scraper — Menus, Reviews & Leads

memo23/uber-eats-scraper

Uber Eats scraper for restaurants and menus. Search by city or paste store URLs. One row per store with priced dishes, ratings, reviews, phone, hours, and optional emails plus a lead score. Filter by locale or skip stores you already have. Delivery or pickup. JSON, CSV or Excel.

Muhamed Didovic

281

4.9

(3)

🍴Uber Eats Scraper [RENTAL]

borderline/ubereats-scraper

Rental - Fast and cost-effective Uber Eats Scraper requiring just a search query and location or by url. Instantly retrieve comprehensive restaurant data, including names, ratings, locations, reviews and menus. Seamlessly integrates with tools like n8n, and more, offering a highly efficient solution

borderline

308

4.7

(5)

Ubereats Stores Search By Location And Keyword

datacach/ubereats-stores-search-by-location-and-keyword

Experience instant restaurant insights with Uber Eats Discovery by Location and Keyword Scraper. Enter a search and location to get real-time data—no URLs needed. Perfect for quick market research and competitor analysis, all in one efficient, easy-to-use tool.

DataCach

Uber Eats Scraper

natanielsantos/uber-eats-scraper

This no-code tool allows you to scrape data from Uber Eats restaurants, like name, categories, location, menu items, and more.

Nataniel Santos

232

Food Delivery Scraper

e-commerce/food-delivery-scraper

Scrape restaurant listings, full menus with prices, and customer reviews from food delivery sites — Uber Eats, DoorDash, Deliveroo, Just Eat, Grubhub, Wolt, Glovo, Foodpanda, Zomato, SkipTheDishes, Thuisbezorgd, Lieferando, Takeaway.com and more — by URL, keyword, or delivery address.

E Commerce

5.0

(3)

Uber Eats Full Menu Scraper

solidcode/ubereats-full-menu-scraper

[💰 $2 / 1K] Extract full Uber Eats menus — every item with price, description, photo and add-on options — plus store ratings, reviews, hours, address, cuisines and delivery fees. Scrape by store URL or discover every store around any address.

SolidCode

Uber Eats Phone Number Scraper – Cheapest 📞🍔

contactminerlabs/uber-eats-phone-number-scraper---cheapest

🔍 Scrape Uber Eats Phone Numbers Instantly Enter a keyword & extract phone numbers from Uber Eats restaurants, vendors, and listings, including restaurant, phone number & listing URL 📞 Perfect for restaurant partnerships, food delivery outreach, lead generation & enriching your CRM pipelines 🚀

ContactMinerLabs

Uber Eats Restaurant Scraper

jdtpnjtp/uber-eats-restaurant-scraper

Scrape Uber Eats restaurants and menus by city, search, or store URL. Extract restaurant name, rating, cuisine, address, delivery fee, menu items, prices, and reviews as clean JSON. Pay per result.

Data Forge

UberEats Menu Scraper + Analytics

datacach/ubereats-menu-scraper

Extract full menus from any UberEats store. Paste store URLs, get menu items with prices, images, and sections — plus per-store analytics (price/image coverage, min/max/avg price). Multi-country support. Ideal for price monitoring and competitive restaurant analysis.