# Uber Eats Scraper — Restaurants, Menus, Prices & Ratings (`technicaldost/uber-eats-scraper-restaurants-menus`) Actor

Scrape Uber Eats restaurants for any delivery address: search by food or list all stores nearby, or paste store URLs. Rating, review count, ETA, price level, cuisines, address, hours, phone, promotions and full menus with item prices.

- **URL**: https://apify.com/technicaldost/uber-eats-scraper-restaurants-menus.md
- **Developed by:** [Technical Dost Solutions](https://apify.com/technicaldost) (community)
- **Categories:** Travel, Lead generation
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $2.00 / 1,000 stores

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For examples already wired to this Actor's own input schema, see the [API](#api) section below.

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).

# README

Uber Eats Scraper extracts **restaurants and full menus from Uber Eats** for any delivery location in the countries Uber Eats serves. Enter an **address, city or ZIP code** and **what to search** (e.g. `sushi`, `burger`, `pizza`), or leave the search empty to list **all stores delivering to that address**. You can also paste **store URLs**. For each store you get the **rating, number of ratings, delivery ETA, price level, cuisines, full address with coordinates, opening hours, business phone, promotions**, and optionally the **complete menu with sections, item prices, descriptions, sold-out flags and photos**. No login or API key.

### What you get

- Search by food or cuisine for any address, or list all stores nearby (Uber's home feed).
- Store URLs supported (ubereats.com/store/...).
- Store details: rating and count, ETA, price level ($-$$$$), cuisines, address, latitude/longitude, hours, phone, promotion badges, brand.
- Full menus: section, item name, price, description, options flag, sold-out flag and image.
- Relevance check: stores Uber adds to results that don't mention your term in name, cuisine or menu are skipped and not charged.
- Pay per store; menus cost extra only when you include them. No start fee.

### How to use Uber Eats Scraper

1. Enter a **Delivery location** (e.g. `Times Square, New York` or `1600 Amphitheatre Pkwy, Mountain View, CA`).
2. Add **Search terms** (e.g. `sushi`) or leave empty to get all stores nearby; and/or paste **Store URLs**.
3. Choose whether to **Include full menus**, and set **Max stores per search**.
4. Run and export to JSON, CSV or Excel, or send to Google Sheets, Make, Zapier or an AI agent.

### Input example

```json
{
  "location": "Times Square, New York",
  "searchTerms": [
    "sushi",
    "burger"
  ],
  "maxStoresPerSearch": 50,
  "includeMenu": true
}
```

All fields are described in the **Input** tab.

### Output example

```json
{
  "storeUuid": "45f9f355-d4e5-4ac0-a1d1-43e92ca63137",
  "name": "RA Sushi Times Square (3043)",
  "url": "https://www.ubereats.com/store/ra-sushi-times-square-3043/RfnzVdTlSsCh0UPpLKYxNw",
  "rating": 4.52,
  "ratingCount": "120+",
  "etaMinMinutes": 30,
  "etaMaxMinutes": 49,
  "isOrderable": true,
  "availability": "ACCEPTING_ORDERS",
  "promotion": "$12 off $65+",
  "badges": [
    "30 min",
    "$12 off $65+"
  ],
  "imageUrl": "https://tb-static.uber.com/prod/image-proc/processed_images/951133982681646f14689194ef70979f/30be7d11a3ed6f6183354d1933fbb6c7.jpeg",
  "priceBucket": "$$",
  "cuisines": [
    "Japanese",
    "Sushi",
    "Asian"
  ],
  "address": "1501 Broadway, New York, NY 10036",
  "streetAddress": "1501 Broadway",
  "city": "New York",
  "region": "NY",
  "postalCode": "10036",
  "country": "US",
  "latitude": 40.7566,
  "longitude": -73.9866,
  "phone": "+12125551234",
  "isOpen": true,
  "workingHoursTagline": "Open until 11:00 PM",
  "hours": [
    {
      "days": "Every day",
      "open": "11:00-23:00"
    }
  ],
  "etaText": "25–40 Min",
  "deliveryFeeText": null,
  "isDeliveryThirdParty": false,
  "currency": "USD",
  "brand": "RA Sushi",
  "menuItemsCount": 183,
  "menu": [
    {
      "itemUuid": "7f6c...",
      "name": "Spicy Tuna Roll",
      "section": "Sushi Rolls",
      "price": 12.95,
      "priceText": "$12.95",
      "description": "Spicy tuna, cucumber, scallions.",
      "isSoldOut": false,
      "hasOptions": false,
      "imageUrl": null
    }
  ],
  "deliveryLocation": "Times Square, New York City, NY 10036, USA",
  "source": "sushi",
  "scrapedAt": "2026-10-26T21:40:00.000Z"
}
```

#### Output fields

| Field | Description |
|---|---|
| `storeUuid` | Uber Eats store ID. |
| `name` | Store name. |
| `url` | Store URL. |
| `rating` | Average rating, 1-5. |
| `ratingCount` | Number of ratings as shown, e.g. 15,000+. |
| `etaMinMinutes` | Delivery ETA, minimum minutes. |
| `etaMaxMinutes` | Delivery ETA, maximum minutes. |
| `isOrderable` | Orderable now. |
| `availability` | Availability state. |
| `promotion` | Promotion badge, e.g. $12 off $65+. |
| `badges` | All badges shown on the card. |
| `imageUrl` | Store image. |
| `priceBucket` | Price level, $ to $$$$. |
| `cuisines` | Cuisines and store type. |
| `address` | Full address. |
| `streetAddress` | Street address. |
| `city` | City. |
| `region` | State or region. |
| `postalCode` | Postal code. |
| `country` | Country code. |
| `latitude` | Latitude. |
| `longitude` | Longitude. |
| `phone` | Business phone. |
| `isOpen` | Open now. |
| `workingHoursTagline` | E.g. Open until 10:45 PM. |
| `hours` | Opening hours by day range (24h). |
| `etaText` | ETA text from the store page. |
| `deliveryFeeText` | Delivery fee text, when shown. |
| `isDeliveryThirdParty` | Store's own couriers. |
| `currency` | Menu currency. |
| `brand` | Chain or brand. |
| `menuItemsCount` | Menu items saved. |
| `menu` | Menu items: name, section, price, description, sold-out flag, image. |
| `deliveryLocation` | Address Uber resolved your location to. |
| `source` | Search term, 'nearby' or the store URL. |
| `scrapedAt` | When the row was scraped. |

Export results as JSON, CSV, Excel, XML or HTML, or read them with the API.

### Use cases

- Restaurant market research: who delivers what, where, at which price level and rating.
- Menu price monitoring and competitor benchmarking for restaurant brands and ghost kitchens.
- Lead generation for restaurant suppliers, POS and delivery-software companies (business address and phone).
- Food-tech and analytics: cuisine mix, ratings and ETAs by neighborhood; schedule recurring runs.
- Promotion tracking: which stores run discounts like "$12 off $65+".

### How much does Uber Eats Scraper cost?

This Actor uses **pay-per-event** pricing: **$0.002 per store** ($2 per 1,000). Platform usage is included. A full menu adds **$0.001 per store** (only when it is included). There is no start fee. Stores that Uber returns but that do not match your search term (e.g. a pet shop for "sushi") are skipped and not charged.

Set **Maximum cost per run** in the run options to cap your spend; the Actor stops when the limit is reached.

### Use Uber Eats Scraper with AI agents (MCP)

Give Claude, ChatGPT, Cursor or any MCP client this Actor as a tool through the hosted [Apify MCP server](https://mcp.apify.com):

```bash
claude mcp add --transport http apify "https://mcp.apify.com/?tools=technicaldost/uber-eats-scraper-restaurants-menus" --header "Authorization: Bearer YOUR_APIFY_TOKEN"
```

Or in a JSON MCP config:

```json
{
  "mcpServers": {
    "apify": {
      "url": "https://mcp.apify.com/?tools=technicaldost/uber-eats-scraper-restaurants-menus",
      "headers": { "Authorization": "Bearer YOUR_APIFY_TOKEN" }
    }
  }
}
```

The tool is named `technicaldost--uber-eats-scraper-restaurants-menus`. Ask your agent, for example, to *"run Uber Eats Scraper with {"location": "Times Square, New York", "searchTerms": \["sushi", "burger"], "maxStoresPerSearch": 50, "includeMenu": true}"*.

### Run Uber Eats Scraper via API

```bash
curl -X POST "https://api.apify.com/v2/acts/technicaldost~uber-eats-scraper-restaurants-menus/run-sync-get-dataset-items?token=YOUR_APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"location": "Times Square, New York", "searchTerms": ["sushi", "burger"], "maxStoresPerSearch": 50, "includeMenu": true}'
```

```python
from apify_client import ApifyClient

client = ApifyClient("YOUR_APIFY_TOKEN")
run = client.actor("technicaldost/uber-eats-scraper-restaurants-menus").call(run_input={"location": "Times Square, New York", "searchTerms": ["sushi", "burger"], "maxStoresPerSearch": 50, "includeMenu": True})
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item)
```

```js
import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: 'YOUR_APIFY_TOKEN' });
const run = await client.actor('technicaldost/uber-eats-scraper-restaurants-menus').call({"location": "Times Square, New York", "searchTerms": ["sushi", "burger"], "maxStoresPerSearch": 50, "includeMenu": true});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);
```

### Integrations

Schedule runs (daily, hourly) in Apify Console and send results to Google Sheets, Slack, Make, Zapier, n8n, Airbyte or your own webhook.

### FAQ

#### Do I need an Uber Eats account?

No. The Actor uses the same public data the Uber Eats website shows logged-out visitors.

#### How should I write the location?

Like you would on ubereats.com: a street address, landmark or "City, State ZIP". A bare ZIP code can match a street number elsewhere; the resolved address is saved in deliveryLocation so you can check it.

#### Why do I get fewer stores than Uber shows?

Uber mixes in loosely related stores (grocery or pet shops for "sushi"). With full details on, the Actor keeps only stores whose name, cuisine or menu mention your term, and does not charge for the rest. They are listed in the ERRORS record.

#### What does ratingCount look like?

Uber shows rounded counts such as "15,000+"; the value is kept as text.

#### Are delivery fees included?

Uber shows fees only for some stores and addresses; when shown they are in deliveryFeeText or badges.

#### Which countries work?

Any Uber Eats market: enter a local address. Prices are in the store's currency (currency field).

#### Is it legal to scrape this data?

The Actor collects publicly available information only and does not log in or bypass access controls. Use the data in line with the website's terms and the laws that apply to you, especially when processing personal data.

### Related Actors

More tools from the same developer that work well together with this one:

- [Swiggy Zomato Menu Price Monitor India](https://apify.com/technicaldost/swiggy-zomato-menu-price-monitor-india): Monitor Swiggy restaurants in any Indian area: cost for two, live offers and discounts, rating, cuisines, delivery time and open status.
- [Google Maps Business Scraper](https://apify.com/technicaldost/google-maps-business-scraper): Find local businesses by search term, such as "dentist in Chicago": name, address, phone, website, email, opening hours and coordinates.
- [Public Business Directory Leads Extractor](https://apify.com/technicaldost/structured-local-business-leads-scraper): Extract local business leads from business pages and store-locator directories: name, address, phone, email, website, category and rating.
- [Local Business Finder (OpenStreetMap)](https://apify.com/technicaldost/osm-local-business-finder): Find local businesses by category and city from OpenStreetMap, a free and legal alternative to Google Maps scraping.

# Actor input Schema

## `location` (type: `string`):

Address, landmark or "City, State ZIP" Uber Eats delivers to. Required for searching; not needed for store URLs.

## `searchTerms` (type: `array`):

Food, cuisine or restaurant names, e.g. sushi, burger, Thai. Leave empty to list all stores delivering to the location.

## `startUrls` (type: `array`):

Uber Eats store URLs, e.g. https://www.ubereats.com/store/katzs-delicatessen/UO5j9laHQCOtgD3H8yWjBw

## `maxStoresPerSearch` (type: `integer`):

Per search term (or for 'all stores nearby'). Up to 2,000.

## `includeMenu` (type: `boolean`):

Adds every menu item with section, price, description and photo (+$0.001 per store).

## `includeDetails` (type: `boolean`):

Address, coordinates, hours, phone, price level and cuisines (1 request per store). Turn off for a fast list from search results only; menus and the relevance check need it.

## Actor input object example

```json
{
  "location": "Times Square, New York",
  "searchTerms": [
    "sushi"
  ],
  "startUrls": [],
  "maxStoresPerSearch": 5,
  "includeMenu": true,
  "includeDetails": true
}
```

# Actor output Schema

## `results` (type: `string`):

No description

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "location": "Times Square, New York",
    "searchTerms": [
        "sushi"
    ],
    "startUrls": [],
    "maxStoresPerSearch": 5
};

// Run the Actor and wait for it to finish
const run = await client.actor("technicaldost/uber-eats-scraper-restaurants-menus").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {
    "location": "Times Square, New York",
    "searchTerms": ["sushi"],
    "startUrls": [],
    "maxStoresPerSearch": 5,
}

# Run the Actor and wait for it to finish
run = client.actor("technicaldost/uber-eats-scraper-restaurants-menus").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "location": "Times Square, New York",
  "searchTerms": [
    "sushi"
  ],
  "startUrls": [],
  "maxStoresPerSearch": 5
}' |
apify call technicaldost/uber-eats-scraper-restaurants-menus --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,technicaldost/uber-eats-scraper-restaurants-menus"
        }
    }
}
```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/tfgL2pceBzArRoSZE/builds/ltFHoUPc4YVNpdQcn/openapi.json