# Google Map Scraper (`leadstrategus/gmap-scraper`) Actor Extract company profiles from Google Maps search results using custom queries. Collect structured business data like name, industry, address, contact details, ratings, and website, ready in dataset/CSV format for lead generation or analysi - **URL**: https://apify.com/leadstrategus/gmap-scraper.md - **Developed by:** [Komala Maran](https://apify.com/leadstrategus) (community) - **Categories:** Lead generation, Automation, Agents - **Stats:** 2 total users, 1 monthly users, 0.0% 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 ## Google Maps Company Scraper (Apify Actor) This Actor scrapes company profiles from Google Maps search results and exports structured business data. ### What it does - Builds a Google Maps query from your input parameters. - Opens the Google Maps search result list for that query. - Scrolls the result feed until it collects enough place links. - Visits each place detail page. - Extracts normalized company fields. - Stores data into the default Apify dataset. ### Extracted output fields Each dataset item contains: - `companyName` - `companyIndustry` - `locationRegion` - `exactAddress` - `servicesOffered` - `companyDomain` - `googleMapsLink` - `contactNumber` - `emailId` - `starRating` - `reviewCount` - `totalCompaniesFound` ### Input schema The Actor expects the following input fields (configured in `.actor/input_schema.json`): - `searchQuery` (string, optional) - Main query term. If empty, query is auto-built. - `location` (string, required) - City/region to search in. - `industryFilter` (string, optional) - Used for auto-built query when `searchQuery` is empty. - `minEmployees` (integer, optional, default `0`) - Appended to the query when greater than 0. - `maxEmployees` (integer, optional) - Used with `minEmployees` for range query text. - `numResults` (integer, required, default `50`, max `500`) - Number of places to extract. - `useProxy` (boolean, default `true`) - Enables Apify Proxy configuration. ### Query-building behavior Query logic: 1. Start with `searchQuery` if provided. 2. Otherwise use: - `" companies"` when `industryFilter` is set, or - `"companies"` fallback. 3. Append `in ` unless the base query already includes the city name. 4. Append employee-size text: - `with to employees` when both min and max are provided. - `with + employees` when only min is provided. ### Anti-block and reliability settings - Optional Apify Proxy support (`useProxy`). - Session pool enabled. - Persistent cookies per session enabled. - Browser launch args include: - `--disable-blink-features=AutomationControlled` - `--lang=en-US` ### Tech stack - Node.js (ES modules) - Apify SDK (`apify`) - Crawlee (`PlaywrightCrawler`) - Playwright ### Example input ```json { "searchQuery": "AI Companies", "location": "Bangalore, India", "industryFilter": "IT Services", "minEmployees": 500, "maxEmployees": 1000, "numResults": 20, "useProxy": true } ```` ### Notes - Data quality depends on what each Google Maps place profile exposes publicly. - `emailId` is inferred as `info@domain` when website domain is available. - `contactNumber` may be parsed from page text when a direct phone selector is absent. # Actor input Schema ## `searchQuery` (type: `string`): Main keyword(s) to search for (e.g. 'AI Companies'). The actor will automatically append location and employee range. Leave empty to auto-build from Industry Filter + Location. ## `location` (type: `string`): City or region to search within. Automatically appended to the query. ## `industryFilter` (type: `string`): Auto-builds the query when Search Query is empty. E.g. 'IT Services' → 'IT Services companies in Bangalore...' ## `minEmployees` (type: `integer`): Appended to query as 'with N to M employees' or 'with N+ employees'. Set 0 to omit. ## `maxEmployees` (type: `integer`): Combined with Minimum to produce 'with 500 to 1000 employees'. Leave empty for no upper bound. ## `numResults` (type: `integer`): How many companies to extract. Maximum 500. ## `useProxy` (type: `boolean`): Strongly recommended. Uses residential proxies to avoid rate limits and bot detection. ## Actor input object example ```json { "searchQuery": "AI Companies", "location": "Bangalore, India", "industryFilter": "IT Services", "minEmployees": 500, "maxEmployees": 1000, "numResults": 20, "useProxy": true } ``` # 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("leadstrategus/gmap-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("leadstrategus/gmap-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 leadstrategus/gmap-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=leadstrategus/gmap-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Google Map Scraper", "description": "Extract company profiles from Google Maps search results using custom queries. Collect structured business data like name, industry, address, contact details, ratings, and website, ready in dataset/CSV format for lead generation or analysi", "version": "0.0", "x-build-id": "MKgZG2JZFcUiHJ5MZ" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/leadstrategus~gmap-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-leadstrategus-gmap-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/leadstrategus~gmap-scraper/runs": { "post": { "operationId": "runs-sync-leadstrategus-gmap-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/leadstrategus~gmap-scraper/run-sync": { "post": { "operationId": "run-sync-leadstrategus-gmap-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "location", "numResults" ], "properties": { "searchQuery": { "title": "Search Query", "type": "string", "description": "Main keyword(s) to search for (e.g. 'AI Companies'). The actor will automatically append location and employee range. Leave empty to auto-build from Industry Filter + Location." }, "location": { "title": "Location", "type": "string", "description": "City or region to search within. Automatically appended to the query.", "default": "Bangalore, India" }, "industryFilter": { "title": "Industry Filter (used when Search Query is empty)", "type": "string", "description": "Auto-builds the query when Search Query is empty. E.g. 'IT Services' → 'IT Services companies in Bangalore...'" }, "minEmployees": { "title": "Minimum Employees", "minimum": 0, "type": "integer", "description": "Appended to query as 'with N to M employees' or 'with N+ employees'. Set 0 to omit.", "default": 0 }, "maxEmployees": { "title": "Maximum Employees (optional)", "type": "integer", "description": "Combined with Minimum to produce 'with 500 to 1000 employees'. Leave empty for no upper bound." }, "numResults": { "title": "Number of Results", "minimum": 1, "maximum": 500, "type": "integer", "description": "How many companies to extract. Maximum 500.", "default": 50 }, "useProxy": { "title": "Use Apify Proxy", "type": "boolean", "description": "Strongly recommended. Uses residential proxies to avoid rate limits and bot detection.", "default": 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 } } } } } } } } } } ```