Google Maps Restaurant Scraper — Reviews

Extract thousands of restaurant contacts, phone numbers, addresses, websites, ratings, and more from Google Maps in minutes. Perfect for B2B sales prospecting, lead generation, and market research.

What This Actor Does

The Google Maps Restaurant Scraper extracts comprehensive restaurant data from Google Maps including:

• Restaurant names and contact information (phone numbers, websites)
• Full addresses with city, state, ZIP code, and country
• GPS coordinates (latitude and longitude) for mapping
• Ratings and review counts from Google
• Cuisine types and categories for segmentation
• Open/closed status for real-time availability

Why Choose This Actor?

Key Features

• 🚀 Fast Extraction - Get hundreds of restaurant records in minutes
• 🎯 Accurate Data - Real-time scraping directly from Google Maps
• 📊 Structured Output - Clean JSON format ready for analysis
• 🌍 Global Coverage - Scrape restaurants from any location worldwide
• 💰 Cost Effective - Pay only for results you get, no hidden fees
• ⚡ No Setup Required - API keys pre-configured, start scraping immediately

Use Cases

Lead Generation & Sales:

• Build restaurant prospect lists for B2B sales teams
• Generate leads for restaurant suppliers (POS systems, food delivery, marketing)
• Create databases for restaurant franchise opportunities

Market Research:

• Competitive analysis across restaurant chains
• Market saturation analysis by cuisine type or location
• Track ratings and reviews trends

Business Development:

• Restaurant directory creation
• Partnership and sponsorship prospecting
• Event catering and venue research

How It Works

1. Enter your search - Provide a keyword (e.g., "Italian restaurants") and location (e.g., "Manhattan, NY")
2. Run the scraper - Our system queries Google Maps via Bright Data SERP API
3. Get results - Receive structured JSON data with all restaurant information

Input Parameters

Parameter	Type	Required	Default	Description
searchQuery	string	Yes	"restaurants"	What to search for (e.g., "pizza", "Italian restaurants", "Chinese food")
location	string	Yes	"New York, NY, USA"	Geographic area to search (e.g., "Los Angeles, CA", "Chicago, IL")
maxResults	integer	No	50	Maximum restaurants to extract (1-500)
scrapeReviews	boolean	No	false	Enable review extraction (coming soon)
scrapePhotos	boolean	No	false	Enable photo URLs (coming soon)

Output Data Schema

Each restaurant record contains:

Field	Type	Description
restaurant_name	string	Full restaurant name
address	string	Full street address
city	string	City name
state	string	State/province
postal_code	string	ZIP/postal code
country	string	Country
latitude	number	GPS latitude
longitude	number	GPS longitude
phone	string	Contact phone number
website	string	Restaurant website URL
rating	number	Star rating (1-5)
review_count	integer	Total review count
cuisine_type	string	Cuisine category
is_open	boolean	Current open status
scraped_at	string	ISO timestamp
source_url	string	Google Maps search URL

SEO Keywords

This actor helps you find and extract data for:

• Restaurant lead generation
• Google Maps business scraping
• Restaurant contact databases
• Local restaurant lists
• Restaurant phone numbers
• Restaurant websites
• Restaurant ratings data
• B2B restaurant sales leads
• Restaurant market research
• Food business intelligence
• Restaurant prospecting tools
• Google Places data extraction
• Restaurant directory building
• Competitive restaurant analysis
• Restaurant chain research

Example Searches

Search Query	Location	Use Case
"Italian restaurants"	"Manhattan, NY"	Fine dining lead generation
"Pizza delivery"	"Los Angeles, CA"	Delivery service prospecting
"Sushi restaurants"	"San Francisco, CA"	Japanese cuisine market analysis
"Coffee shops"	"Chicago, IL"	Cafe chain expansion research
"Fast food"	"Texas, USA"	Quick service restaurant directory

Example Output

{
  "restaurant_name": "Manhatta",
  "address": "28 Liberty St 60th floor, New York, NY 10005",
  "city": "New York",
  "state": "NY",
  "postal_code": "10005",
  "country": "United States",
  "latitude": 40.707997399999996,
  "longitude": -74.00888259999999,
  "phone": "+12122305788",
  "website": "https://www.manhattarestaurant.com/restaurant-menu/",
  "rating": 4.7,
  "review_count": null,
  "cuisine_type": "New American restaurant, Fine dining restaurant, Lounge",
  "is_open": true,
  "scraped_at": "2026-04-15T10:08:21.161Z",
  "source_url": "https://www.google.com/maps/search/restaurants+in+New+York"
}

Technical Details

• Powered by: Bright Data SERP API (enterprise-grade web scraping)
• Data source: Google Maps (real-time, accurate)
• Output format: Structured JSON
• Rate: Up to 500 restaurants per search
• Response time: Typically 10-30 seconds

Pricing

Pay per result - Only pay for restaurants successfully scraped.

Contact for enterprise pricing with volume discounts.

Related Actors

• Google Maps Reviews Scraper - Extract reviews
• Google Maps Places Extractor - More features

Support

Need help or have questions? Contact the developer for assistance with:

• Custom scraping configurations
• Large volume data extraction
• Integration with your systems
• White-label solutions

License

MIT License - free to use in commercial and personal projects.

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Made with ❤️ for marketers, researchers, and sales professionals who need restaurant data fast.

What is Google Maps Restaurant Scraper?

Google Maps Restaurant Scraper turns the target data into structured, reusable results on Apify. Use it when you need repeatable collection for analysts, developers, agencies, researchers, and AI-agent workflows without maintaining a custom scraper or one-off integration. Run it manually, schedule recurring jobs, call it through the Apify API, or connect it to an AI agent through the Apify MCP server.

The Actor stores results in an Apify dataset, where they can be previewed and exported as JSON, CSV, Excel, XML, or RSS. Availability and completeness depend on the source, supplied inputs, public visibility, authentication requirements, and upstream rate limits.

Use cases for Google Maps Restaurant Scraper

• Build structured datasets for research, reporting, enrichment, or monitoring.
• Automate repetitive collection with schedules, webhooks, and API calls.
• Feed clean records into spreadsheets, databases, CRMs, BI tools, AI agents, or RAG pipelines.
• Track changes over time by running the same validated input on a schedule.
• Replace fragile manual copy-and-paste work with a reproducible Apify workflow.

How to use Google Maps Restaurant Scraper

1. Open the Actor input page and choose a focused, valid target.
2. Set a conservative result limit for the first run.
3. Start the Actor and inspect the dataset for coverage and field availability.
4. Export the results or connect the dataset to your downstream system.
5. Scale gradually and use scheduling, pagination, or proxies when supported.

Important input options

• searchQuery — What to search for on Google Maps. Example: 'Italian restaurants in Manhattan'. Use this when searching by keyword.
• location — Geographic area to search in. Examples: 'Manhattan, NY', 'Los Angeles, CA'.
• maxResults — Maximum number of restaurants to extract per search.
• scrapeReviews — When enabled, fetches individual reviews with name, rating, date, and text.
• maxReviewsPerPlace — Maximum reviews to fetch per restaurant.
• scrapePhotos — When enabled, collects photo URLs from the restaurant gallery.
• language — Language code for results (e.g. 'en', 'es', 'fr').
• brightdataApiKey — Your Bright Data API key. Get it from https://brightdata.com/cp/setting/users

API and automation example

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: process.env.APIFY_TOKEN });
const run = await client.actor('muhammadafzal/google-maps-restaurant-scraper').call({
  // Add the same input fields you use in the Apify Console.
});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);

Related Apify Actors

Use these dedicated tools when a neighboring data source or workflow is a better match:

• OpenTable Restaurants, Ratings & Reviews Scraper
• Arizona ROC Contractor License Scraper
• Idealista Scraper — Extract Listings, Prices & Agency Contacts
• Realtor & Real Estate Agent Lead Scraper — Verified Emails
• Craigslist Scraper — Extract Listings, Prices & Locations
• Instagram Followers & Following Scraper — With Cookies
• Facebook Ads Library Scraper — Meta Ad Intelligence Tool
• Leads Finder Pro - B2B Leads with Emails [Apollo Alternative]
• Yellow Pages US Scraper — Business Leads & Reviews
• Justia Lawyer Directory Scraper — Attorney Leads

Frequently asked questions

How many results can I scrape with Google Maps Restaurant Scraper?

The practical total depends on the source, input limits, pagination, available records, run timeout, and upstream restrictions. Start with a small run, verify the output, and increase the limit gradually.

Can I integrate Google Maps Restaurant Scraper with other apps?

Yes. Use Apify integrations, webhooks, schedules, dataset exports, Make, Zapier, Google Sheets, cloud storage, or your own application.

Can I use Google Maps Restaurant Scraper with the Apify API?

Yes. Start runs with the Apify REST API or an official Apify client, then retrieve records from the run's default dataset. Keep your API token in a secret or environment variable.

Can I use Google Maps Restaurant Scraper through an MCP Server?

Yes. The Apify MCP server can expose the Actor to compatible AI clients and agents. Review the input and expected cost before allowing an autonomous workflow to run it at scale.

Do I need proxies?

It depends on the source and volume. Use the default configuration first. For larger or geographically sensitive jobs, select an appropriate proxy configuration only when the Actor supports it.

Is it legal to scrape this data?

Scraping rules vary by source, jurisdiction, data type, and intended use. Collect only data you are authorized to access, respect applicable terms and privacy laws, and avoid restricted or personal data misuse. This documentation is not legal advice.

Your feedback

If a field is missing, a source layout has changed, or you need a supported use case documented, open an issue on the Actor page with a reproducible input and run ID.