Pricing

$5.00 / 1,000 restaurants

Try for free

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🍴Uber Eats Scraper [PPR]

Try for free

Pay per result - Fast and cost-effective Uber Eats Scraper requiring just a search query and location or using stores urls. Instantly retrieve comprehensive restaurant data, including names, phone, ratings, locations, and menus. Seamlessly integrates, offering a highly efficient data solution.

Pricing

$5.00 / 1,000 restaurants

Rating

5.0

(3)

Developer

borderline

Actor stats

Bookmarked

399

Total users

Monthly active users

4.8 hours

Issues response

13 hours ago

Last modified

Categories

Lead generation

Automation

You can access the 🍴Uber Eats Scraper [PPR] programmatically from your own applications by using the Apify API. You can also choose the language preference from below. To use the Apify API, you’ll need an Apify account and your API token, found in Integrations settings in Apify Console.

Python

JavaScript

CLI

OpenAPI

HTTP

MCP

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          "locale": {
            "title": "🗺️ Locale",
            "enum": [
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              "de-LU"
            ],
            "type": "string",
            "description": "Select locale (default is en-US). Applies to both search and URL mode."
          },
          "address": {
            "title": "📍 Delivery address",
            "type": "string",
            "description": "Delivery address to search in. (ex: Address, City, Zip Code, etc.) Required when not using urls."
          },
          "query": {
            "title": "🔎 Search query",
            "type": "string",
            "description": "Query to search for. (ex: McDonald's, pizza, etc.) Optional when using address."
          },
          "maxRows": {
            "title": "📈 Maximum number of rows (restaurants/stores)",
            "type": "integer",
            "description": "Maximum number of restaurants to scrape when using address/query. (0 = all). Not used in Option 2 (URLs): result count = number of input URLs."
          },
          "urls": {
            "title": "🔗 Store URLs",
            "type": "array",
            "description": "List of Uber Eats restaurant/store page URLs to scrape. When provided, address and query are ignored.",
            "items": {
              "type": "string"
            }
          },
          "getMenuCustomizations": {
            "title": "🧩 Menu customizations",
            "type": "boolean",
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          }
        }
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                "example": "2025-01-08T00:00:00.000Z"
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                "example": "READY"
              },
              "meta": {
                "type": "object",
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                    "type": "string",
                    "example": "API"
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                  "userAgent": {
                    "type": "string"
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                }
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🍴Uber Eats Scraper [PPR] OpenAPI definition

OpenAPI is a standard for designing and describing RESTful APIs, allowing developers to define API structure, endpoints, and data formats in a machine-readable way. It simplifies API development, integration, and documentation.

OpenAPI is effective when used with AI agents and GPTs by standardizing how these systems interact with various APIs, for reliable integrations and efficient communication.

By defining machine-readable API specifications, OpenAPI allows AI models like GPTs to understand and use varied data sources, improving accuracy. This accelerates development, reduces errors, and provides context-aware responses, making OpenAPI a core component for AI applications.

You can download the OpenAPI definitions for 🍴Uber Eats Scraper [PPR] from the options below:

OpenAPI.json

If you’d like to learn more about how OpenAPI powers GPTs, read our blog post.

You can also check out our other API clients:

🍴Uber Eats Scraper [PPR] API in Python

🍴Uber Eats Scraper [PPR] API in JavaScript

🍴Uber Eats Scraper [PPR] API through CLI

🍴Uber Eats Scraper [PPR] API

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