# Uber Eats Scraper — Menu & Location Data (`bovi/uber-menu-scraper`) Actor

Extract Uber Eats menus, item prices, categories, and location data. Features URL-list and query inputs, structured Dataset output, HTTP-first transport, automatic browser escalation, and mandatory Apify RESIDENTIAL proxy routing.

- **URL**: https://apify.com/bovi/uber-menu-scraper.md
- **Developed by:** [Vitalii Bondarev](https://apify.com/bovi) (community)
- **Categories:** Travel, E-commerce
- **Stats:** 2 total users, 1 monthly users, 50.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $2.72 / 1,000 uber eats scraper — menu & location data

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.
Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have.

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 — Menu & Location Data

Extract Uber Eats menus, item prices, categories, and location data. Features URL-list and query inputs, structured Dataset output, HTTP-first transport, automatic browser escalation, and mandatory Apify RESIDENTIAL proxy routing.

### What it does

Uber Eats Scraper — Menu & Location Data is a data-collection tool for the travel and ecommerce category. The inputs let you set the scope and preferences for a run, while the results provide organized records that are easier to review and use.

### Input

Provide the values that define the scope and preferences for the run. Review each option before starting so the resulting dataset matches the information you want to analyze or reuse.

| Name | Type | Description | Default |
| --- | --- | --- | --- |
| maxItems | integer | Maximum number of records to save to the Dataset. | 100 |
| proxyConfiguration | object | Apify proxy configuration. Residential proxies are enabled by default. | {"useApifyProxy":true,"apifyProxyGroups":\["RESIDENTIAL"]} |
| query | string | Best-effort restaurant discovery query. Uber may return no stores when a delivery location is unavailable. | — |
| urls | array | Public Uber store page URLs to scrape. Explicit URLs continue even when query discovery returns no stores. | `https://www.ubereats.com/store/zuckers-bagels-fidis/YK9UYIbxTd2Gappp2N4pgQ` |

### Output

A successful run produces a dataset of structured items collected according to your inputs. You can review the records, use them in analysis, or pass them to another part of your workflow. The exact fields depend on the source data and the options selected for the run.

### Usage

1. Open the actor page.
2. Keep the prefilled US store URL for a working default run, or replace it with one or more concrete Uber Eats store URLs.
3. Run the actor and wait for the collection to finish.
4. Download the results from the dataset and use the records in your preferred workflow.

Search is optional and best-effort. When both `urls` and `query` are supplied, a search page with no discovered stores is logged and saved as diagnostic evidence, while the explicit store URLs are still scraped.

Menu extraction reads Uber's embedded Schema.org JSON-LD (`Restaurant` → `hasMenu` → `MenuSection` → `MenuItem`) and keeps the existing Dataset shape: `restaurant` plus `menu_item` with title, description, price, image URL, and fallback item ID.

### Pricing

Pricing is pay-per-event, so you pay only for results.

# Actor input Schema

## `query` (type: `string`):

Restaurant, store, cuisine, or other public Uber listing search query.

## `urls` (type: `array`):

Public Uber store page URLs to scrape. The prefilled US store keeps the default run independent of best-effort search discovery.

## `maxItems` (type: `integer`):

Maximum number of records to save to the Dataset.

## `proxyConfiguration` (type: `object`):

Apify proxy configuration. Residential proxies are enabled by default.

## Actor input object example

```json
{
  "urls": [
    "https://www.ubereats.com/store/zuckers-bagels-fidis/YK9UYIbxTd2Gappp2N4pgQ"
  ],
  "maxItems": 100,
  "proxyConfiguration": {
    "useApifyProxy": true,
    "apifyProxyGroups": [
      "RESIDENTIAL"
    ]
  }
}
```

# Actor output Schema

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

Dataset of Uber Eats restaurants and menu items (restaurant id/name/rating/category/address/url, menu item id/title/description/price/image).

# 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 = {};

// Run the Actor and wait for it to finish
const run = await client.actor("bovi/uber-menu-scraper").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 = {}

# Run the Actor and wait for it to finish
run = client.actor("bovi/uber-menu-scraper").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 '{}' |
apify call bovi/uber-menu-scraper --silent --output-dataset

```

## MCP server setup

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

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/kdkvWqEpTuDQZcuTV/builds/bM398YmQ942dWTph6/openapi.json