🛵 Foodora Scraper — Restaurants, Menus & Prices

Scrape Foodora restaurants and their menus in bulk as clean, structured JSON, CSV, Excel or XML. Give it a city (Stockholm, Gothenburg, Malmö, Vienna, Graz, Oslo, Bergen, Prague, Brno, Budapest, Debrecen) or exact coordinates, and it returns one tidy row per restaurant — name, cuisines, rating, reviews, address, coordinates, minimum order, delivery fee and open status — plus, on request, every menu item with its price. Sweep a whole city with an optional geo-grid. Perfect for food-market research, competitor and price monitoring, lead generation and automation.

What does Foodora Scraper do?

This actor turns Foodora's restaurant listings into a ready-to-use dataset. Point it at a city or a latitude/longitude, and it collects every restaurant delivering to that area with rich, structured details. Turn on Include menu items and it also pulls each restaurant's full menu — categories, dish names, descriptions and prices — as extra rows. Use the built-in geo-grid to sweep many points across a city and de-duplicate the results automatically, so you get broad, clean coverage in a single run.

What data can you get?

Per restaurant:

Field	Description
id	Restaurant identifier.
code	Short restaurant code.
name	Restaurant name.
cuisines	List of cuisine tags (e.g. Pizza, Sushi, Burgers).
rating	Average customer rating.
reviewCount	Number of ratings.
address	Street address.
latitude	Restaurant latitude.
longitude	Restaurant longitude.
minOrder	Minimum order amount.
deliveryFee	Delivery fee.
isOpen	Whether the restaurant is currently accepting delivery.
url	Link to the restaurant page.

Per menu item (when Include menu items is on):

Field	Description
vendorId	Restaurant the item belongs to.
vendorName	Restaurant name.
category	Menu section (e.g. Pizza, Drinks).
itemName	Dish name.
price	Item price.
description	Dish description, when available.

Use cases

• Food-market research — map the restaurants, cuisines and price points in any city.
• Price & competitor monitoring — track delivery fees, minimum orders and menu prices over time.
• Lead generation — build lists of restaurants with addresses and coordinates for sales outreach.
• Menu & pricing analysis — compare dishes and prices across restaurants and neighbourhoods.
• Dashboards & maps — power location, coverage and demand dashboards from clean coordinates.
• Automation — feed fresh restaurant and menu data into your own pipelines on a schedule.

How to use it

1. Add Foodora Scraper to your Apify account and open its input.
2. Enter a City (e.g. Stockholm), or set Latitude + Longitude for an exact point.
3. Optionally turn on Include menu items to also collect every dish and price.
4. Optionally set Grid radius (km) and Grid step (km) to sweep a whole city.
5. Set Max restaurants to cap the output if you like, then click Run.
6. Export the results as JSON, CSV, Excel or XML.

Input

{
  "city": "Stockholm",
  "includeMenu": true,
  "maxItems": 50
}

Field	Description
city	City to scrape; mapped to a centre coordinate and country.
latitude / longitude	Exact point to search around (overrides city).
country	Two-letter country code (auto-filled from a supported city).
includeMenu	Also collect each restaurant's menu items and prices.
gridRadiusKm	Half-width of a square geo-grid, in km, to cover a whole city. 0 = single point.
gridStep	Spacing in km between grid points.
maxItems	Cap the number of restaurants. 0 = no limit.

What you get

One flat JSON row per restaurant, plus one row per menu item when menus are included — ready to export to CSV, Excel, JSON or XML.

{
  "id": "37697",
  "code": "rlxo",
  "name": "Taco Bell Vasagatan",
  "cuisines": ["Mexican", "Burritos", "Tacos"],
  "rating": 3.7,
  "reviewCount": 585,
  "address": "Vasagatan 14",
  "latitude": 59.331,
  "longitude": 18.058,
  "minOrder": 120,
  "deliveryFee": 59,
  "isOpen": true,
  "url": "https://foodora.se/restaurant/rlxo/taco-bell-vasagatan"
}

{
  "vendorId": "37697",
  "vendorName": "Taco Bell Vasagatan",
  "category": "Tacos",
  "itemName": "Crunchy Taco Supreme",
  "price": 39,
  "description": "Crispy taco shell with seasoned beef, cheese and fresh tomato"
}

FAQ

Which cities and countries are supported? Use a supported city name for one-click setup — Stockholm, Gothenburg, Malmö, Vienna, Graz, Oslo, Bergen, Prague, Brno, Budapest, Debrecen — covering Sweden, Austria, Norway, Czechia and Hungary. For anywhere else Foodora serves, set your own Latitude and Longitude together with the two-letter country code.

How do I cover a whole city? Set Grid radius (km) to sweep a square of points around the centre, and Grid step (km) to control how dense the sweep is. Results are de-duplicated across all points automatically.

How do I get menu prices? Turn on Include menu items. Each restaurant then adds extra rows, one per dish, with its category, name, price and description.

How many restaurants can I get? As many as deliver to the area. Use Max restaurants to cap the run, or leave it at 0 for everything found.

What export formats are available? JSON, CSV, Excel and XML, plus programmatic access through the Apify API.

Can I use this with n8n? Yes. Run it from the Apify n8n community node or trigger it over HTTP, then pass the dataset items straight into your n8n workflow to enrich records, monitor prices or drive downstream steps.

Can I connect this to my other tools? It works with Make, Zapier, Slack, Airbyte, GitHub, Google Drive and many more, plus the Apify API, JavaScript/Python clients and MCP. Or use webhooks to trigger an action whenever a run finishes.

How fresh is the data? Every run collects live listings and menus at run time. Re-run on a schedule to keep your copy current.

Related Actors

• Google Maps Scraper — businesses, ratings, reviews and contacts from Google Maps.
• Amazon Product Scraper — product details, prices and ratings in bulk.
• Google Maps Reviews — pull reviews for any place at scale.

Notes

Original clean-room implementation. Collects only publicly available restaurant and menu information; you are responsible for compliant use. All trademarks, including Foodora, belong to their respective owners and this actor is not affiliated with or endorsed by them.