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.

• 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, …) with locale-aware proxy routing
• Extract store UUID / menuItem UUID, title, URL, rating, price bucket, ETA, formatted address, cuisine / city slugs
• Resolve delivery place from a human address or encoded pl (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.

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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:

1. Validates your input (mode, locale, city/address/store identifiers, max results)
2. Enforces free-tier caps when you are on a free Apify plan
3. Collects public Uber Eats surfaces through a managed scrape backend with residential egress
4. Parses listing / menu signals into normalized Dataset records
5. 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.

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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	—	✅*	✅*	—	—	✅
Menu sections / customizations	—	—	✅*	✅	—	—

*When present on the page or script state. Feed/search prefer address-aware discovery; city/category use SEO listing pages. Grocery / Alcohol verticals via search are experimental.

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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.

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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

• Google Maps Scraper
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Prefer another specialized scraper?

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

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How to scrape Uber Eats (no code required)

1. Create a free Apify account
2. Open Uber Eats Scraper
3. Choose a mode: city, category, cuisines, location, feed, search, store, menu_item, brand, resolve_place, or startUrls
4. Choose a locale (default us)
5. Enter a citySlug, cuisineSlug, query + address/pl, storeUrl / storeUuid, or startUrls
6. (Optional) Set maxResults, maxPages, vertical, includeCuisines, enrichDetails
7. Click Start and download the Dataset as JSON, CSV, Excel, or JSONL

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

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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
Results 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.

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Input examples

City SEO listings (US)

{
  "mode": "city",
  "locale": "us",
  "citySlug": "denver-co",
  "maxResults": 20,
  "maxPages": 2
}

Cuisine category (Canada)

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

Delivery search by address

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

Store menu

{
  "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"
}

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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 / etaText / priceBucket	Listing signals when present
formattedAddress	Address text when present
scrapedAt	ISO timestamp

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

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Tips for best results

• Prefer short verification runs (maxResults: 5) before large jobs
• For Canada addresses, use locale=ca (and matching proxyCountry) — US locale + Canadian address often stalls place resolve
• Prefer address over hand-crafted pl unless you already have a valid encoded place
• Use SEO city/category modes when you do not need a delivery pin; use feed/search when results must match an address
• Treat GROCERY / ALCOHOL search verticals as experimental
• Production jobs should use a normal Actor run (Dataset + KV). Standby /search is for capped Live-view previews only

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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. Residential egress is handled by the Actor backend. You do not mint Apify proxy in the Actor input for normal runs.

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.

What about Grocery or Alcohol?

Search vertical values GROCERY / ALCOHOL are experimental. Restaurant discovery (ALL / RESTAURANTS) is the primary path.

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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.

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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

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