Starbucks Store & Menu Scraper

Scrapes Starbucks store locations and menu items with prices and nutritional info.

API Source

• Stores: https://www.starbucks.com/bff/locations
• Menu: https://www.starbucks.com/menu
• API Key: Not required

Input Parameters

Parameter	Type	Default	Description
mode	enum	"stores"	What to scrape: "stores", "menu", or "both"
location	string	"Seattle, WA"	City, ZIP code, or address for store search
radius	integer	10	Search radius in miles (1-100)
menuCategory	enum	""	Menu category: "" (all), "drinks", "food", "at-home-coffee", "merchandise"
limit	integer	50	Maximum number of items to return (max 500)
proxyConfiguration	object	{ useApifyProxy: true }	Proxy settings

Example Input

{
  "mode": "stores",
  "location": "New York, NY",
  "radius": 5,
  "limit": 100
}

{
  "mode": "menu",
  "menuCategory": "drinks",
  "limit": 200
}

{
  "mode": "both",
  "location": "Los Angeles, CA",
  "radius": 10,
  "menuCategory": "food",
  "limit": 50
}

Output

Store Output Fields

Field	Type	Description
type	string	Always "store"
storeNumber	string	Unique store identifier
name	string	Store name
address.street	string	Street address line 1
address.street2	string	Street address line 2
address.city	string	City
address.state	string	State/province code
address.postalCode	string	ZIP/postal code
address.country	string	Country code
coordinates.lat	number	Latitude
coordinates.lng	number	Longitude
phone	string	Phone number
hours	string/object	Operating hours
features	array	Store features (e.g., Mobile Order, Drive Thru)
mobileOrderEnabled	boolean	Mobile ordering available
driveThru	boolean	Has drive-thru
wifi	boolean	Has WiFi
distance	number	Distance from search location
scrapedAt	string	ISO timestamp of scrape

Example Store Output

{
  "type": "store",
  "storeNumber": "12345-67890",
  "name": "Pike Place",
  "address": {
    "street": "1912 Pike Place",
    "street2": null,
    "city": "Seattle",
    "state": "WA",
    "postalCode": "98101",
    "country": "US"
  },
  "coordinates": {
    "lat": 47.6097,
    "lng": -122.3422
  },
  "phone": "(206) 448-8762",
  "hours": "Open 24 Hours",
  "features": ["Mobile Order", "WiFi", "Drive Thru"],
  "mobileOrderEnabled": true,
  "driveThru": true,
  "wifi": true,
  "distance": 0.5,
  "scrapedAt": "2026-01-25T12:00:00.000Z"
}

Menu Item Output Fields

Field	Type	Description
type	string	Always "menu_item"
name	string	Item name
price	string	Price (numeric value)
calories	string	Calorie count
image	string	Image URL
url	string	Product page URL
category	string	Menu category
scrapedAt	string	ISO timestamp of scrape

Example Menu Item Output

{
  "type": "menu_item",
  "name": "Caffe Latte",
  "price": "5.45",
  "calories": "190",
  "image": "https://www.starbucks.com/weblx/images/products/caffe-latte.jpg",
  "url": "https://www.starbucks.com/menu/product/407/hot",
  "category": "drinks",
  "scrapedAt": "2026-01-25T12:00:00.000Z"
}

Usage

Run on Apify

1. Go to the actor page on Apify
2. Configure input parameters
3. Click "Run"
4. Download results from the Dataset tab

Run Locally

# Install dependencies
npm install

# Set input in storage/key_value_stores/default/INPUT.json
echo '{"mode": "stores", "location": "Seattle, WA"}' > storage/key_value_stores/default/INPUT.json

# Run
npm start

Tech Stack

• Node.js 18+
• Apify SDK 3.x
• Crawlee 3.x
• Playwright (for menu scraping)

Notes

• Store locations use the Starbucks BFF API with geocoding via OpenStreetMap Nominatim
• Menu scraping uses Playwright to render the React-based menu pages
• Residential proxies recommended for reliable scraping
• Rate limiting is built-in with random delays between requests