# Google Maps Restaurant Scraper (`muhammadafzal/google-maps-restaurant-scraper`) Actor - **URL**: https://apify.com/muhammadafzal/google-maps-restaurant-scraper.md - **Developed by:** [Muhammad Afzal](https://apify.com/muhammadafzal) (community) - **Categories:** Lead generation, Travel, Real estate - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $3.50 / 1,000 results This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage. 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 ## Google Maps Restaurant Scraper - Extract Restaurant Leads & Business Data **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 ```json { "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](https://apify.com/compass/Google-Maps-Reviews-Scraper) - Extract reviews - [Google Maps Places Extractor](https://apify.com/compass/google-maps-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. *** **Made with ❤️ for marketers, researchers, and sales professionals who need restaurant data fast.** # Actor input Schema ## `searchQuery` (type: `string`): What to search for on Google Maps. Example: 'Italian restaurants in Manhattan'. Use this when searching by keyword. ## `location` (type: `string`): Geographic area to search in. Examples: 'Manhattan, NY', 'Los Angeles, CA'. ## `maxResults` (type: `integer`): Maximum number of restaurants to extract per search. ## `scrapeReviews` (type: `boolean`): When enabled, fetches individual reviews with name, rating, date, and text. ## `maxReviewsPerPlace` (type: `integer`): Maximum reviews to fetch per restaurant. ## `scrapePhotos` (type: `boolean`): When enabled, collects photo URLs from the restaurant gallery. ## `language` (type: `string`): Language code for results (e.g. 'en', 'es', 'fr'). ## `brightdataApiKey` (type: `string`): Your Bright Data API key. Get it from https://brightdata.com/cp/setting/users ## `brightdataSerpApiId` (type: `string`): Your Bright Data SERP API ID from your SERP API page. Get it from https://brightdata.com/cp/zones ## Actor input object example ```json { "searchQuery": "restaurants", "location": "New York, NY, USA", "maxResults": 50, "scrapeReviews": false, "maxReviewsPerPlace": 5, "scrapePhotos": false, "language": "en" } ``` # 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 = { "searchQuery": "restaurants", "location": "New York, NY, USA", "brightdataApiKey": "", "brightdataSerpApiId": "" }; // Run the Actor and wait for it to finish const run = await client.actor("muhammadafzal/google-maps-restaurant-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 = { "searchQuery": "restaurants", "location": "New York, NY, USA", "brightdataApiKey": "", "brightdataSerpApiId": "", } # Run the Actor and wait for it to finish run = client.actor("muhammadafzal/google-maps-restaurant-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 '{ "searchQuery": "restaurants", "location": "New York, NY, USA", "brightdataApiKey": "", "brightdataSerpApiId": "" }' | apify call muhammadafzal/google-maps-restaurant-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=muhammadafzal/google-maps-restaurant-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Google Maps Restaurant Scraper", "description": null, "version": "1.0", "x-build-id": "owqQ2VSdUjYH4FvB8" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/muhammadafzal~google-maps-restaurant-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-muhammadafzal-google-maps-restaurant-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/muhammadafzal~google-maps-restaurant-scraper/runs": { "post": { "operationId": "runs-sync-muhammadafzal-google-maps-restaurant-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/muhammadafzal~google-maps-restaurant-scraper/run-sync": { "post": { "operationId": "run-sync-muhammadafzal-google-maps-restaurant-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "properties": { "searchQuery": { "title": "Search Query", "type": "string", "description": "What to search for on Google Maps. Example: 'Italian restaurants in Manhattan'. Use this when searching by keyword." }, "location": { "title": "Location", "type": "string", "description": "Geographic area to search in. Examples: 'Manhattan, NY', 'Los Angeles, CA'." }, "maxResults": { "title": "Max Results", "minimum": 1, "maximum": 500, "type": "integer", "description": "Maximum number of restaurants to extract per search.", "default": 50 }, "scrapeReviews": { "title": "Scrape Reviews", "type": "boolean", "description": "When enabled, fetches individual reviews with name, rating, date, and text.", "default": false }, "maxReviewsPerPlace": { "title": "Max Reviews Per Place", "minimum": 1, "maximum": 100, "type": "integer", "description": "Maximum reviews to fetch per restaurant.", "default": 5 }, "scrapePhotos": { "title": "Scrape Photos", "type": "boolean", "description": "When enabled, collects photo URLs from the restaurant gallery.", "default": false }, "language": { "title": "Language", "type": "string", "description": "Language code for results (e.g. 'en', 'es', 'fr').", "default": "en" }, "brightdataApiKey": { "title": "Bright Data API Key", "type": "string", "description": "Your Bright Data API key. Get it from https://brightdata.com/cp/setting/users" }, "brightdataSerpApiId": { "title": "Bright Data SERP API ID", "type": "string", "description": "Your Bright Data SERP API ID from your SERP API page. Get it from https://brightdata.com/cp/zones" } } }, "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 } } } } } } } } } } ```