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Uber Eats Scraper API

Turn any Uber Eats restaurant or location search into structured JSON: menus, item prices, modifiers, delivery fees, ETAs, ratings, and ranked results — per delivery address.

Restaurants & menusLive pricingReviews & ratingsGeo-segmented
▸ Overview

Uber Eats operates in thousands of cities worldwide, with menus, pricing, and availability that vary by delivery address and time of day. The Uber Eats Scraper API resolves restaurant pages and location searches into validated JSON with full menus, item-level pricing, fees, and ETAs.

It's built for menu-intelligence, dynamic-pricing, and market-analysis teams tracking the delivery economy. Menus and fees are resolved at request time and geo-segmented down to the neighborhood.

Uber Eats Scraper API · request
# POST a target — get validated JSON back
curl https://api.crawlzo.com/v4/scrape \
  -H "Authorization: Bearer $CRAWLZO_KEY" \
  -d '{
  "url": "https://www.ubereats.com/",
  "type": "restaurant",
  "geo": "us-ny"
  }'

// ← response
{
  "status": "ok",
  "data": {
    "name": "...",
    "rating": 4.5,
    "review_count": 820,
    "cuisine": "...",
    "delivery_fee": 2.99,
    "eta_min": 25,
    "menu_items": 142
  }
}
"type": "restaurant", "geo": "us-ny"
▸ What you can extract

Every public field, structured for you.

Uber Eats data parsed into clean, validated JSON. Pull any group below on its own, or combine them in a single request.

Restaurant / store details

  • Name, cuisine, address, coordinates
  • Rating, review count, price level
  • Hours, delivery zone, contact
  • Photos and cover imagery

Menu & items

  • Categories, items, descriptions
  • Item price, modifiers, options
  • Dietary tags and popularity
  • Item images

Reviews & ratings

  • Review text, rating, author, date
  • Rating distribution
  • Full review pagination

Delivery & pricing

  • Delivery fee and service fee
  • Minimum order and ETA
  • Promotions and offers

Search results

  • Ranked restaurants per location
  • Cuisine, price, rating filters
  • Sponsored vs. organic flag
  • Pagination across result pages
▸ Built on the Crawlzo engine

The hard parts, already solved.

▸ What teams build with it

Common use cases.

[ 01 ]

Menu and item-price intelligence

[ 02 ]

Delivery-fee and commission analysis

[ 03 ]

Restaurant coverage and availability mapping

[ 04 ]

Competitive market and share analysis

▸ FAQ

Uber Eats scraping, answered.

Structured JSON straight from the API, or pushed to your stack natively — S3, BigQuery, Snowflake, Postgres, Kafka, or any HTTPS webhook. Call it from Python, Node, Go, Rust, or any HTTP client. The data lands where your pipeline already lives.

No. You pay for valid, schema-passing rows only. Retries, blocks, CAPTCHAs, and 5xxs are on us. If a run doesn't return data that conforms to the schema, it isn't billed.

Every request routes through the same engine behind our Web Unblocker API: compliant residential IPs, real browser fingerprints, TLS-level evasion, behaviour modelling, and built-in CAPTCHA solving. Hard targets become routine.

Yes. We respect robots policies, rate budgets, and ToS-aware allow/deny lists. We deliver and move on — no row-level retention beyond your replay window. GDPR DPA, PII redaction, and custom data residency available on request.

UBER EATS DATA · ON TAP

Start pulling Uber Eats data this week.

Tell us the Uber Eats surface you need and the shape you want it in. We'll come back in 24 hours with a sampled output, a scoped plan, and a price. Pilot in week one.

Pay only for data delivered99.99% uptime SLA99% success rate100M+ proxies