# Restaurants Google Maps Scraper (`mukeshrana90/restaurants-google-maps-scraper`) Actor Scrape restaurants from Google Maps with email, social media, cuisine, price range, dietary options, menu highlights, review sentiment, online ordering / reservation detection, metro area classification, and restaurant-type enrichment. - **URL**: https://apify.com/mukeshrana90/restaurants-google-maps-scraper.md - **Developed by:** [Mukesh Kumar](https://apify.com/mukeshrana90) (community) - **Categories:** Lead generation, Automation - **Stats:** 3 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $5.00 / 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 ## Restaurants Google Maps Scraper Scrape restaurants from Google Maps and enrich each result with emails, social media links, cuisine, price range, dietary options, menu highlights, customer review sentiment, online ordering / reservation detection, metro area classification, and restaurant type. Built for restaurant marketing agencies, food-delivery sales teams, hospitality recruiters, restaurant tech SaaS, and food critics that need structured, CRM-ready data from Google Maps. ### What data do you get? Each scraped restaurant includes up to **35+ fields** across these categories: | Category | Fields | |----------|--------| | **Identity** | name, category, cuisine | | **Location** | address, city, state, postalCode, country, latitude, longitude | | **Contact** | phone, website, email | | **Social Media** | instagram, facebook, linkedin, twitter | | **Restaurant** | priceRange, dietaryOptions, menuHighlights | | **Niche** | hasOnlineOrdering, orderingPlatform, orderingUrl, hasReservation, reservationPlatform, reservationUrl, isMetroArea, metroName, metroTier, restaurantType, restaurantTypeLabel, restaurantConfidence | | **Reputation** | rating, reviewCount, reviewSentiment (label, score, topThemes, snippets) | | **Operational** | hours, isOpenNow | | **Metadata** | placeId, mapsUrl, scrapedAt, searchTerm, searchLocation | ### Sample output ```json { "name": "Carbone", "category": "Italian restaurant", "cuisine": "Italian, Pasta", "address": "181 Thompson St", "fullAddress": "181 Thompson St, New York, NY 10012, United States", "city": "New York", "state": "NY", "country": "United States", "postalCode": "10012", "latitude": 40.7280123, "longitude": -74.0001234, "phone": "+12122541313", "website": "https://carbonenewyork.com/", "email": "reservations@carbonenewyork.com", "instagram": "https://instagram.com/carbonenewyork", "facebook": "https://facebook.com/carbonenewyork", "linkedin": null, "twitter": null, "priceRange": "$$$$", "dietaryOptions": ["vegetarian", "gluten-free"], "menuHighlights": ["Spicy Rigatoni Vodka", "Veal Parmesan", "Caesar Salad"], "hasOnlineOrdering": false, "orderingPlatform": null, "orderingUrl": null, "hasReservation": true, "reservationPlatform": "resy.com", "reservationUrl": "https://resy.com/cities/ny/carbone", "isMetroArea": true, "metroName": "New York Metro", "metroTier": 1, "restaurantType": "fine_dining", "restaurantTypeLabel": "Fine Dining", "restaurantConfidence": "medium", "rating": 4.6, "reviewCount": 3200, "reviewSentiment": { "label": "Positive", "score": 86, "topThemes": ["foodQuality", "service", "ambience"], "reviewsAnalysed": 10, "avgRating": 4.6, "snippets": { "positive": [ "Absolutely incredible Italian-American food. The spicy rigatoni is legendary...", "Service was attentive and the atmosphere felt like a 1950s supper club..." ], "negative": [] } }, "hours": { "Monday": "5:30–11 pm", "Tuesday": "5:30–11 pm", "Wednesday": "5:30–11 pm", "Thursday": "5:30–11 pm", "Friday": "5:30 pm–12 am", "Saturday": "5:30 pm–12 am", "Sunday": "5:30–11 pm" }, "isOpenNow": true, "placeId": "0x89c2598ad12f1a8b:0x123abc456def7890", "mapsUrl": "https://www.google.com/maps/place/Carbone/...", "scrapedAt": "2026-05-23T10:56:47.935Z", "searchTerm": "italian restaurant", "searchLocation": "New York, USA" } ```` ### How to use 1. **Search terms** — Enter restaurant categories like `italian restaurant`, `sushi bar`, `pizza`, `vegan restaurant`, `steakhouse`. 2. **Locations** — Enter cities or regions like `New York, USA`, `London, UK`, `Mumbai, India`. 3. **Max results** — Set how many places to return (up to 500). 4. **Toggle enrichment** — Enable or disable email extraction, social media, restaurant fields, and niche classification independently. ### Input example ```json { "searchTerms": ["italian restaurant", "sushi bar"], "locations": ["New York, USA", "Los Angeles, USA"], "maxResults": 100, "minRating": 4.0, "enrichEmails": true, "enrichSocials": true, "enrichRestaurant": true, "enrichRestaurantNiche": true } ``` ### Enrichment pipeline The scraper runs a 4-stage enrichment pipeline for each restaurant: #### 1. Google Maps scraping Extracts name, category, address, phone, website, rating, reviews, hours, coordinates, and place ID directly from Google Maps search results. #### 2. Restaurant enrichment - **Cuisine** — Extracted from Maps category tags and "About" section attributes. - **Price range** — Read from the Maps header ($, $$, $$$, $$$$). Maps "Inexpensive / Moderate / Expensive / Very Expensive" labels are mapped to the matching dollar count. - **Dietary options** — Scanned from Maps service-options attributes, then falls back to the restaurant website (`/menu`, `/dietary`, `/allergens` pages). Captures vegan, vegetarian, halal, kosher, gluten-free, dairy-free, keto, paleo, and more. - **Menu highlights** — Pulls Google Maps "Popular dishes" tiles, with a fallback that scans `/menu` pages on the restaurant website for headline dish names. - **Review sentiment** — Clicks the Reviews tab on Maps, extracts up to 10 reviews, and runs keyword-based sentiment analysis. Returns a sentiment label (Positive/Mixed/Negative), a 0-100 score, top themes (foodQuality, service, ambience, value, waitTime, cleanliness), and representative snippets. #### 3. Restaurant niche classification - **Online ordering** — Checks for ordering buttons on Maps and scans the website for delivery platforms (DoorDash, UberEats, Grubhub, Toast, ChowNow, Square Ordering, Deliveroo, Just Eat, Swiggy, Zomato). - **Reservation** — Checks for reservation buttons on Maps and scans the website for booking platforms (OpenTable, Resy, SevenRooms, Tock, TheFork, Yelp Reservations). - **Metro area** — Classifies the restaurant location against a curated database of metro areas across USA, UK, India, UAE, Australia, and Canada with tier rankings (1-3). - **Restaurant type** — Classifies as `fine_dining`, `casual`, `fast_food`, `cafe`, `food_truck`, `bar`, or `unknown` based on name keywords, category, cuisine, and price range. #### 4. Contact enrichment - **Email** — Visits the restaurant website and extracts the best email address using domain matching and scoring. Prefers role mailboxes like `reservations@`, `chef@`, `owner@`, `manager@`, `catering@`, `events@`. Tries `/contact`, `/contact-us`, `/about`, `/about-us` pages as fallback. Filters out generic addresses (noreply, support, etc.). - **Social media** — Extracts Instagram, Facebook, LinkedIn, and Twitter/X profile links from the restaurant website. ### Use cases - **Restaurant marketing agencies** — Build targeted lead lists of restaurants by cuisine, price range, and online presence. - **Food-delivery sales teams** — Find restaurants without online ordering for DoorDash / UberEats / Toast onboarding. - **Reservation platform sales** — Find restaurants without OpenTable / Resy for outbound pitches. - **Hospitality recruiters** — Filter by restaurant type (fine dining vs casual) for chef / FOH placement. - **Market research** — Analyze restaurant density, cuisine mix, sentiment, and competitive landscape by metro area. ### Proxy This actor requires **residential proxies** to avoid Google Maps blocks. Apify residential proxy is configured by default. For best results, use the `RESIDENTIAL` proxy group. ### Cost estimate Each Google Maps search page processes up to ~20 results. With all enrichment enabled, each restaurant takes 20-40 seconds (website visits for email, dietary options, menu highlights). A typical run of 100 results with full enrichment uses approximately 0.5-1.0 compute units on Apify. ### Limitations - Google Maps may return different results based on proxy location. - Review sentiment analysis uses keyword matching (no LLM) — works best with 5+ reviews. - Dietary detection relies on keyword matching and may miss restaurants that only show dietary tags on menu PDFs or images. - Metro area classification covers major metros in USA, UK, India, UAE, Australia, and Canada. # Actor input Schema ## `searchTerms` (type: `array`): Restaurant categories to search for on Google Maps (e.g. italian restaurant, sushi bar, pizza, vegan restaurant, steakhouse) ## `locations` (type: `array`): Cities, regions, or countries to search in (e.g. New York, USA or London, UK) ## `maxResults` (type: `integer`): Maximum number of places to scrape in total across all search term + location combinations ## `minRating` (type: `number`): Only include restaurants with this Google rating or above (0 = no filter) ## `enrichEmails` (type: `boolean`): Visit each restaurant website and extract the best email address (checks homepage, /contact, /about pages) ## `enrichSocials` (type: `boolean`): Extract Instagram, Facebook, LinkedIn, and Twitter/X profile links from restaurant websites ## `enrichRestaurant` (type: `boolean`): Extract cuisine, price range, dietary options (vegan / vegetarian / halal / kosher / gluten-free), menu highlights, and customer review sentiment analysis from Google Maps and restaurant websites ## `enrichRestaurantNiche` (type: `boolean`): Detect online ordering / delivery (DoorDash, UberEats, Grubhub, Toast) and reservations (OpenTable, Resy, SevenRooms), classify metro area tier, and categorize restaurant type (fine dining, casual, fast food, cafe, food truck) ## `proxyConfig` (type: `object`): Residential proxies recommended to avoid Google Maps blocks ## Actor input object example ```json { "searchTerms": [ "italian restaurant", "sushi bar" ], "locations": [ "New York, USA" ], "maxResults": 20, "minRating": 0, "enrichEmails": false, "enrichSocials": false, "enrichRestaurant": false, "enrichRestaurantNiche": false, "proxyConfig": { "useApifyProxy": true } } ``` # Actor output Schema ## `defaultDataset` (type: `string`): Dataset containing scraped restaurants with 35+ fields including contact info, social media, cuisine, price range, dietary options, menu highlights, review sentiment, online ordering / reservation detection, metro classification, and restaurant type. # 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 = { "searchTerms": [ "italian restaurant", "sushi bar" ], "locations": [ "New York, USA" ], "maxResults": 20, "minRating": 0 }; // Run the Actor and wait for it to finish const run = await client.actor("mukeshrana90/restaurants-google-maps-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 = { "searchTerms": [ "italian restaurant", "sushi bar", ], "locations": ["New York, USA"], "maxResults": 20, "minRating": 0, } # Run the Actor and wait for it to finish run = client.actor("mukeshrana90/restaurants-google-maps-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 '{ "searchTerms": [ "italian restaurant", "sushi bar" ], "locations": [ "New York, USA" ], "maxResults": 20, "minRating": 0 }' | apify call mukeshrana90/restaurants-google-maps-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=mukeshrana90/restaurants-google-maps-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Restaurants Google Maps Scraper", "description": "Scrape restaurants from Google Maps with email, social media, cuisine, price range, dietary options, menu highlights, review sentiment, online ordering / reservation detection, metro area classification, and restaurant-type enrichment.", "version": "1.0", "x-build-id": "q57pY8ZfFPlczT6hh" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/mukeshrana90~restaurants-google-maps-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-mukeshrana90-restaurants-google-maps-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/mukeshrana90~restaurants-google-maps-scraper/runs": { "post": { "operationId": "runs-sync-mukeshrana90-restaurants-google-maps-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/mukeshrana90~restaurants-google-maps-scraper/run-sync": { "post": { "operationId": "run-sync-mukeshrana90-restaurants-google-maps-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": { "searchTerms": { "title": "Search terms", "type": "array", "description": "Restaurant categories to search for on Google Maps (e.g. italian restaurant, sushi bar, pizza, vegan restaurant, steakhouse)", "default": [ "italian restaurant" ], "items": { "type": "string" } }, "locations": { "title": "Locations", "type": "array", "description": "Cities, regions, or countries to search in (e.g. New York, USA or London, UK)", "default": [ "New York, USA" ], "items": { "type": "string" } }, "maxResults": { "title": "Max results per search", "minimum": 1, "maximum": 500, "type": "integer", "description": "Maximum number of places to scrape in total across all search term + location combinations", "default": 50 }, "minRating": { "title": "Minimum rating filter", "minimum": 0, "maximum": 5, "type": "number", "description": "Only include restaurants with this Google rating or above (0 = no filter)", "default": 0 }, "enrichEmails": { "title": "Extract emails", "type": "boolean", "description": "Visit each restaurant website and extract the best email address (checks homepage, /contact, /about pages)", "default": false }, "enrichSocials": { "title": "Extract social media links", "type": "boolean", "description": "Extract Instagram, Facebook, LinkedIn, and Twitter/X profile links from restaurant websites", "default": false }, "enrichRestaurant": { "title": "Restaurant enrichment", "type": "boolean", "description": "Extract cuisine, price range, dietary options (vegan / vegetarian / halal / kosher / gluten-free), menu highlights, and customer review sentiment analysis from Google Maps and restaurant websites", "default": false }, "enrichRestaurantNiche": { "title": "Restaurant niche classification", "type": "boolean", "description": "Detect online ordering / delivery (DoorDash, UberEats, Grubhub, Toast) and reservations (OpenTable, Resy, SevenRooms), classify metro area tier, and categorize restaurant type (fine dining, casual, fast food, cafe, food truck)", "default": false }, "proxyConfig": { "title": "Proxy configuration", "type": "object", "description": "Residential proxies recommended to avoid Google Maps blocks", "default": { "useApifyProxy": true } } } }, "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 } } } } } } } } } } ```