# Google Search Scraper (`microworlds/google-search-scraper`) Actor Scrape Google Search pages - **URL**: https://apify.com/microworlds/google-search-scraper.md - **Developed by:** [Caleb David](https://apify.com/microworlds) (community) - **Categories:** Jobs, SEO tools, Other - **Stats:** 91 total users, 3 monthly users, 0.0% runs succeeded, 4 bookmarks - **User rating**: No ratings yet ## Pricing from $0.40 / 1,000 search result scrapeds This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have. 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 ## 🚀 Apollo Lead Scraper > Extract verified business leads from Apollo.io with precision and ease. ### ✨ Features - 🎯 **Catch-All Domain Protection**: Exclude catch-all email domains for better quality leads - 📊 **Rich Lead Data**: Get comprehensive information including: - Professional details (name, title, LinkedIn profile) - Contact information (work email, work phone number) - Company information - Employment history - Social media profiles - 🔒 **Data Privacy**: Secure handling of sensitive information ### 🎯 Use Cases - **Sales Prospecting**: Find qualified leads with verified contact information - **Market Research**: Gather insights about companies and their employees - **Lead Generation**: Build targeted contact lists for your business - **Competitor Analysis**: Monitor industry professionals and their movements ### ⚙️ Configuration #### Input Parameters | Parameter | Description | Default | | ---------------------------------- | --------------------------------- | ------- | | `url` | Apollo.io search URL to scrape | - | | `max_result` | Maximum number of leads to scrape | 1000 | | `contact_email_status_v2_verified` | Filter for verified emails only | true | | `contact_email_exclude_catch_all` | Exclude catch-all email domains | true | #### Sample Input ```json { "url": "https://app.apollo.io/#/people?sortByField=recommendations_score&sortAscending=false&page=1&contactEmailStatusV2[]=verified&personTitles[]=sales&contactEmailExcludeCatchAll=true", "max_result": 1000, "contact_email_status_v2_verified": true, "contact_email_exclude_catch_all": true } ```` ### 📊 Output Format The actor returns detailed lead information in JSON format, including: - Personal information (name, title, location) - Contact details (email, phone) - Professional profiles (LinkedIn, Twitter, GitHub) - Company information - Employment history - Department and function details #### Sample Output ```json { "id": "67a683b4359ad8000147cb69", "first_name": "Satya", "last_name": "Nadella", "name": "Satya Nadella", "linkedin_url": "http://www.linkedin.com/in/satyanadella", "title": "Chairman and CEO", "email_status": "verified", "photo_url": "https://media.licdn.com/dms/image/v2/C5603AQHHUuOSlRVA1w/profile-displayphoto-shrink_200_200/profile-displayphoto-shrink_200_200/0/1579726625398?e=2147483647\u0026v=beta\u0026t=Rr7WT9uBM0byOij0oT_KirejIMVE4HK4r8NGIp0zjdI", "twitter_url": null, "github_url": null, "facebook_url": null, "extrapolated_email_confidence": null, "headline": "Chairman and CEO", "email": "", "organization_id": "62337760d02af100a5ca2468", "employment_history": [ { "_id": "686b8a84c0705d00017a5b25", "created_at": null, "current": true, "degree": null, "description": null, "emails": null, "end_date": null, "grade_level": null, "kind": null, "major": null, "organization_id": "5ed3616347cfca0001112fcb", "organization_name": "University of Chicago", "raw_address": null, "start_date": "2018-01-01", "title": "Member Board Of Trustees", "updated_at": null, "id": "686b8a84c0705d00017a5b25", "key": "686b8a84c0705d00017a5b25" }, ... ], "state": "Washington", "city": "Redmond", "country": "United States", "organization": { "id": "62337760d02af100a5ca2468", "name": "Microsoft", "website_url": "http://www.microsoft.com", "blog_url": null, "angellist_url": null, "linkedin_url": "http://www.linkedin.com/company/microsoft", "twitter_url": "https://twitter.com/microsoft", "facebook_url": "https://facebook.com/Microsoft", "primary_phone": { "number": "+1 800-642-7676", "source": "Scraped", "sanitized_number": "+18006427676" }, "languages": ["English"], "alexa_ranking": 32, "phone": "+1 800-642-7676", "linkedin_uid": "1035", "founded_year": 1975, "publicly_traded_symbol": "MSFT", "publicly_traded_exchange": "nasdaq", "logo_url": "https://zenprospect-production.s3.amazonaws.com/uploads/pictures/6865ede9b183b800016b6902/picture", "crunchbase_url": null, "primary_domain": "microsoft.com", "sanitized_phone": "+18006427676", "market_cap": "3707.7B", "industry": "information technology \u0026 services", "estimated_num_employees": 228000, "keywords": [ "business software", "developer tools", "home", ... ], "industries": ["information technology \u0026 services", "internet"], "secondary_industries": ["internet"], "snippets_loaded": true, "industry_tag_id": "5567cd4773696439b10b0000", "industry_tag_hash": { "information technology \u0026 services": "5567cd4773696439b10b0000", "internet": "5567cd4d736964397e020000" }, "retail_location_count": 96, "raw_address": "1 Microsoft Way, Redmond, Washington 98052, US", "street_address": "1 Microsoft Way", "city": "Redmond", "state": "Washington", "postal_code": "98052", "country": "United States", "owned_by_organization_id": null, "short_description": "Microsoft Corporation is a leading American multinational technology company based in Redmond, Washington. Founded in 1975 by Bill Gates and Paul Allen,....", "suborganizations": [ { "id": "54a135e969702d449459eb00", "name": "CAPPTAIN", "website_url": "http://www.capptain.com" }, ... ], "num_suborganizations": 126, "annual_revenue_printed": "198B", "annual_revenue": 198000000000.0, "technology_names": [ "ASP.NET", "Adobe Media Optimizer", "Akamai", ... ], "current_technologies": [ { "uid": "asp_net", "name": "ASP.NET", "category": "Frameworks and Programming Languages" }, { "uid": "adobe_media_optimizer", "name": "Adobe Media Optimizer", "category": "Search Marketing" }, ... ], "org_chart_root_people_ids": ["67a683b4359ad8000147cb69"], "org_chart_sector": "OrgChart::SectorHierarchy::Rules::IT", "org_chart_removed": false, "org_chart_show_department_filter": true, "organization_headcount_six_month_growth": null, "organization_headcount_twelve_month_growth": null, "organization_headcount_twenty_four_month_growth": null }, "intent_strength": null, "show_intent": false, "email_domain_catchall": false, "revealed_for_current_team": true, "departments": ["c_suite"], "subdepartments": ["executive"], "functions": [], "seniority": "c_suite" } ``` ### 🚀 Getting Started 1. **Configure Input**: Set up your Apollo.io search URL and desired parameters 2. **Run the Actor**: Execute the scraper with your configuration 3. **Download Results**: Get your leads in JSON, Excel, CSV or HTML table formats 4. **Integrate**: Use the data in your CRM or sales automation tools ### 🔒 Privacy & Compliance - All sensitive information is properly redacted in the output - The actor respects Apollo.io's terms of service - Data is processed securely and confidentially ### 📈 Performance - **Reliability**: Built-in error handling and retry mechanisms - **Scalability**: Handle large datasets efficiently ### 🕒 Timeout - It can take up to 20 minutes to pull 1000 leads. Please configure your run limit accordingly. ### 💰 Pricing Pricing is tiered based on your current Apify plan. - **Free plan**: $5/1000 leads - **Starter**: $1/1000 leads - **Scale**: $0.9/1000 leads - **Business**: $0.8/1000 leads #### 💡 Notes - Minimum `100` leads per run. If you get less than 100 leads, you'll still be charged for at least 100 leads. Please ensure your search URL yields at least 100 leads. - Free users have a daily run limit of `2` and are limited by `100` leads per run, charged at `$5/1,000` results. ### ⚠️ Disclaimer The actor pulls emails at 'best-efforts'. Not all leads may include emails. Currently, the it can pull upto ~50% of emails (can be more). ### 🤝 Support Need help? Open an issue on the "Issues" tab. *** *Built with ❤️ for sales and marketing professionals* # Actor input Schema ## `url` (type: `string`): Enter the Apollo URL you want to scrape. ## `max_result` (type: `integer`): This value lets you set the maximum number of results to retrieve. ## `include_email` (type: `boolean`): If you want to include emails in the results, leave this checked. ## `contact_email_status_v2_verified` (type: `boolean`): This filters Apollo results to only include verified emails. That will help you to get better results. ## `contact_email_exclude_catch_all` (type: `boolean`): This filters Apollo results to exclude catch-all domains. That will help you to get better results. ## Actor input object example ```json { "url": "https://app.apollo.io/#/people?sortByField=recommendations_score&sortAscending=false&page=1&contactEmailStatusV2[]=verified&personTitles[]=sales&contactEmailExcludeCatchAll=true", "max_result": 100, "include_email": true, "contact_email_status_v2_verified": true, "contact_email_exclude_catch_all": 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 = { "url": "https://app.apollo.io/#/people?sortByField=recommendations_score&sortAscending=false&page=1&contactEmailStatusV2[]=verified&personTitles[]=sales&contactEmailExcludeCatchAll=true", "max_result": 100 }; // Run the Actor and wait for it to finish const run = await client.actor("microworlds/google-search-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 = { "url": "https://app.apollo.io/#/people?sortByField=recommendations_score&sortAscending=false&page=1&contactEmailStatusV2[]=verified&personTitles[]=sales&contactEmailExcludeCatchAll=true", "max_result": 100, } # Run the Actor and wait for it to finish run = client.actor("microworlds/google-search-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 '{ "url": "https://app.apollo.io/#/people?sortByField=recommendations_score&sortAscending=false&page=1&contactEmailStatusV2[]=verified&personTitles[]=sales&contactEmailExcludeCatchAll=true", "max_result": 100 }' | apify call microworlds/google-search-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=microworlds/google-search-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Google Search Scraper", "description": "Scrape Google Search pages", "version": "0.0", "x-build-id": "FED8YsstmHWEM0nzd" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/microworlds~google-search-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-microworlds-google-search-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/microworlds~google-search-scraper/runs": { "post": { "operationId": "runs-sync-microworlds-google-search-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/microworlds~google-search-scraper/run-sync": { "post": { "operationId": "run-sync-microworlds-google-search-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "url": { "title": "Apollo URL", "type": "string", "description": "Enter the Apollo URL you want to scrape." }, "max_result": { "title": "Maximum number of results", "type": "integer", "description": "This value lets you set the maximum number of results to retrieve.", "default": 100 }, "include_email": { "title": "Include Email", "type": "boolean", "description": "If you want to include emails in the results, leave this checked.", "default": true }, "contact_email_status_v2_verified": { "title": "Verified Emails (leave checked for max emails)", "type": "boolean", "description": "This filters Apollo results to only include verified emails. That will help you to get better results.", "default": true }, "contact_email_exclude_catch_all": { "title": "Exlude Catch-All domains (leave checked for max emails)", "type": "boolean", "description": "This filters Apollo results to exclude catch-all domains. That will help you to get better results.", "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 } } } } } } } } } } ```