# Uber Eats Store Scraper (`moving_beacon-owner1/uber-eats-store-scraper`) Actor Scrape restaurant details and complete menus from Uber Eats store URLs. Extract restaurant information, ratings, cuisines, contact details, menu categories, item descriptions, prices, and store metadata with support for residential proxies and bulk store processing. - **URL**: https://apify.com/moving\_beacon-owner1/uber-eats-store-scraper.md - **Developed by:** [Jamshaid Arif](https://apify.com/moving_beacon-owner1) (community) - **Categories:** Developer tools, E-commerce, Automation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $10.00 / 1,000 results 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/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. 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. Actors are written with capital "A". ## 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. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## Uber Eats Store Scraper An [Apify](https://apify.com) actor that scrapes restaurant details and full menus from Uber Eats store URLs. ### Input | Field | Type | Description | |-------|------|-------------| | `storeUrls` | array | Uber Eats store URLs or bare store UUIDs (required) | | `maxItemsPerStore` | integer | Cap menu items saved per store (0 = no limit) | | `proxyConfiguration` | object | Proxy settings; defaults to Apify RESIDENTIAL | Example input: ```json { "storeUrls": [ "https://www.ubereats.com/store/some-slug/abcdef12-3456-7890-abcd-ef1234567890" ], "maxItemsPerStore": 0, "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": ["RESIDENTIAL"] } } ```` How to get a store URL: open a restaurant on ubereats.com and copy the address bar. The trailing segment is the store UUID, which is all the actor needs. ### Output One dataset record per store: ```json { "name": "Floppy Burgers", "address": "...", "rating": 4.4, "phone": "...", "cuisines": ["Burgers"], "itemCount": 16, "items": [ { "name": "La Mozzarella", "description": "...", "price": 10500.0, "section": "HAMBURGUESAS AMERICANAS" } ], "storeUuid": "abcdef12-...", "storeUrl": "https://www.ubereats.com/store/..." } ``` Note: `price` is divided by 100 from Uber's integer minor units. For currencies without minor units (e.g. CLP), values may appear scaled — adjust in `parse_store` if needed for your region. # Actor input Schema ## `storeUrls` (type: `array`): One or more Uber Eats store URLs (or bare store UUIDs). Get a URL by opening a restaurant on ubereats.com and copying it from the address bar. ## `maxItemsPerStore` (type: `integer`): Limit how many menu items to save per store (0 = no limit). ## `splitItems` (type: `boolean`): If true (default), each menu item is its own dataset record with store fields repeated — exports cleanly to CSV/Excel. If false, one record per store with a nested items list. ## `proxyConfiguration` (type: `object`): Uber Eats blocks datacenter IPs. RESIDENTIAL proxies are strongly recommended. ## Actor input object example ```json { "storeUrls": [ "https://www.ubereats.com/store/mcdonalds-700-west-4th-street/D9vYPnglREqMPS4BFm77Fg" ], "maxItemsPerStore": 0, "splitItems": true, "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } } ``` # 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 '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "storeUrls": [ "https://www.ubereats.com/store/mcdonalds-700-west-4th-street/D9vYPnglREqMPS4BFm77Fg" ], "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } }; // Run the Actor and wait for it to finish const run = await client.actor("moving_beacon-owner1/uber-eats-store-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 '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "storeUrls": ["https://www.ubereats.com/store/mcdonalds-700-west-4th-street/D9vYPnglREqMPS4BFm77Fg"], "proxyConfiguration": { "useApifyProxy": True, "apifyProxyGroups": ["RESIDENTIAL"], }, } # Run the Actor and wait for it to finish run = client.actor("moving_beacon-owner1/uber-eats-store-scraper").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "storeUrls": [ "https://www.ubereats.com/store/mcdonalds-700-west-4th-street/D9vYPnglREqMPS4BFm77Fg" ], "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } }' | apify call moving_beacon-owner1/uber-eats-store-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=moving_beacon-owner1/uber-eats-store-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Uber Eats Store Scraper", "description": "Scrape restaurant details and complete menus from Uber Eats store URLs. Extract restaurant information, ratings, cuisines, contact details, menu categories, item descriptions, prices, and store metadata with support for residential proxies and bulk store processing.", "version": "0.0", "x-build-id": "AmSl8WxDGgJwFaAPF" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/moving_beacon-owner1~uber-eats-store-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-moving_beacon-owner1-uber-eats-store-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/moving_beacon-owner1~uber-eats-store-scraper/runs": { "post": { "operationId": "runs-sync-moving_beacon-owner1-uber-eats-store-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/moving_beacon-owner1~uber-eats-store-scraper/run-sync": { "post": { "operationId": "run-sync-moving_beacon-owner1-uber-eats-store-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "required": [ "storeUrls" ], "properties": { "storeUrls": { "title": "Uber Eats store URLs", "type": "array", "description": "One or more Uber Eats store URLs (or bare store UUIDs). Get a URL by opening a restaurant on ubereats.com and copying it from the address bar.", "items": { "type": "string" } }, "maxItemsPerStore": { "title": "Max menu items per store", "minimum": 0, "type": "integer", "description": "Limit how many menu items to save per store (0 = no limit).", "default": 0 }, "splitItems": { "title": "One row per menu item", "type": "boolean", "description": "If true (default), each menu item is its own dataset record with store fields repeated — exports cleanly to CSV/Excel. If false, one record per store with a nested items list.", "default": true }, "proxyConfiguration": { "title": "Proxy configuration", "type": "object", "description": "Uber Eats blocks datacenter IPs. RESIDENTIAL proxies are strongly recommended.", "default": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```