# Google Maps Scraper (`lisbuenas/google-maps-scraper`) Actor Extract Google Maps place data from search terms or URLs, including name, category, ratings, address, contact details, coordinates, reviews, and images, with structured dataset output ready for analysis or export. - **URL**: https://apify.com/lisbuenas/google-maps-scraper.md - **Developed by:** [Felipe Lisboa](https://apify.com/lisbuenas) (community) - **Categories:** Automation, SEO tools, Integrations - **Stats:** 1 total users, 0 monthly users, 0.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $1.20 / 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 💠💠 MultiPolygon Ideal for scraping scattered, non-contiguous territories (like an island chain or specific scattered ZIP codes) in a single run. 🔘 Circle (Point) Define a central point coordinate and set a custom radiusKm parameter to scrape perfectly outward from a specific landmark. 🚀 Advanced Premium Add-ons Transform raw maps listings into a highly targeted outbound database using built-in enrichment workflows: 👥 Business Leads & Social Profile Enrichment Automatically matches the scraped website against public professional profiles to uncover executive decision-makers, job titles, and deep social media metrics (follower counts, verification status) across Facebook, Instagram, LinkedIn, TikTok, and YouTube. ✅ Built-in Email Verification Stop bouncing! When verifyLeadsEnrichmentEmails is active, every extracted email runs through an automated validation layer: Charged (Valid Results): ok (deliverable), invalid (non-existent), disposable (temporary). Free of Charge: catch_all, unknown, error. JSON { "email": "james.hill@apify.com", "quality": "good", "result": "ok", "subResult": "accepted_email", "free": false, "role": false } 1. Rich Output & Seamless Integrations View, filter, and extract your data exactly how your team needs it: Flexible Formats: Download cleanly organized datasets in JSON, CSV, Excel, XML, or HTML. Visual Map View: Review your entire scraped footprint on a zoomable, interactive live map inside your console dashboard. Custom Views: Use specialized export toggles like Reviews or Leads to flatten complex tables so every individual review or verified contact gets its own row for seamless CRM importing. 🪢 Ecosystem Connections Connect your data directly to third-party tools using native platform webhooks or our dedicated MCP Server. Seamlessly push freshly scraped leads straight into Zapier, Make, Slack, Google Sheets, Airbyte, or LangChain. ❓ Frequently Asked Questions How does this compare to the official Google Maps API? The official API charges heavily per request and strictly caps your search results to 60 places, no matter how large your radius is. Our scraper has no artificial caps, is vastly more cost-effective, extracts up to thousands of results per region by systematically scanning areas, and pulls data fields like popular time histograms which Google's API hides. How do I scale my scraping speed? To process massive datasets rapidly, increase your run memory up to 8 GB. For multi-city or nationwide campaigns, use the Google Maps Scraper Orchestrator to automatically break your search terms and locations across parallel runs, deduplicate the output, and compile everything into a single, clean file. Is scraping Google Maps data legal? Yes. Web scraping public data is completely legal. Our scraper extracts information that is publicly accessible on the web. However, users should always ensure compliance with regional personal data regulations (like GDPR/CCPA) when collecting direct contact data, and respect Google's general Terms of Use. 🛠️ Developer-Ready API Access Need to trigger scrapes programmatically? Integrate using our dedicated SDKs: Node.js: Use the official apify-client NPM package. Python: Use the official apify-client PyPI package for effortless automation within data science and AI pipelines. """ # Actor input Schema ## `addresses` (type: `array`): Addresses to start with. ## Actor input object example ```json {} ```` # Actor output Schema ## `results` (type: `string`): All scraped places in the default dataset. # 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 = {}; // Run the Actor and wait for it to finish const run = await client.actor("lisbuenas/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 = {} # Run the Actor and wait for it to finish run = client.actor("lisbuenas/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 '{}' | apify call lisbuenas/google-maps-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=lisbuenas/google-maps-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Google Maps Scraper", "description": "Extract Google Maps place data from search terms or URLs, including name, category, ratings, address, contact details, coordinates, reviews, and images, with structured dataset output ready for analysis or export.", "version": "0.0", "x-build-id": "24uzov0gIFruJcsx1" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/lisbuenas~google-maps-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-lisbuenas-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/lisbuenas~google-maps-scraper/runs": { "post": { "operationId": "runs-sync-lisbuenas-google-maps-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/lisbuenas~google-maps-scraper/run-sync": { "post": { "operationId": "run-sync-lisbuenas-google-maps-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "required": [ "addresses" ], "properties": { "addresses": { "title": "Start Addresses", "type": "array", "description": "Addresses to start with.", "items": { "type": "string" } } } }, "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 } } } } } } } } } } ```