# Google Search Crawler (`mrscrap/google-search-crawler`) Actor Crawl any Google search query and extract full page content as clean Markdown. Filter by country, language, and date range. Outputs title, URL, source tag, and full Markdown content for each result. - **URL**: https://apify.com/mrscrap/google-search-crawler.md - **Developed by:** [Mr Scrap](https://apify.com/mrscrap) (community) - **Categories:** SEO tools, Integrations, Automation - **Stats:** 1 total users, 0 monthly users, 0.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing $1.50 / 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 Search Crawler **Turn any Google search into structured, clean Markdown content — automatically.** --- ### What it does Google Search Content Extractor crawls Google search results for any keyword and visits each result page to extract its full content as clean Markdown. No login required. No API key needed. Just a keyword — and get back structured, ready-to-use content in seconds. Built for researchers, content strategists, SEO analysts, and developers who need to aggregate web content at scale without the manual copy-paste grind. --- ### Key Features - **Google SERP crawling** — fetches the top results for any keyword, country, language, and date range - **Full page content extraction** — visits each result URL and returns clean Markdown (navigation, ads, and menus automatically removed) - **Parallel crawling** — up to 10 pages scraped simultaneously for maximum speed - **Smart filtering** — automatically skips CDN assets, image URLs, login-walled pages, and Google-internal links - **Proxy support** — compatible with Apify Datacenter and Residential proxies for high-volume runs - **Structured output** — every result includes title, URL, content, and source tag --- ### Use Cases - **Content research** — aggregate what's being published on any topic in real time - **SEO analysis** — understand what content ranks for your target keywords - **Competitive intelligence** — monitor what your competitors publish - **AI training data** — collect clean Markdown content for LLM fine-tuning or RAG pipelines - **Dashboard automation** — schedule regular runs and pipe results into Google Sheets, Notion, or any database --- ### Input Example ```json { "keyword": "best AI tools for marketing 2024", "country": "us", "language": "en", "date_range": "week", "max_results": 10, "scrape_pages": true, "concurrency": 5 } ```` | Field | Type | Default | Description | |---|---|---|---| | `keyword` | string | required | Search query | | `country` | string | `us` | Google country code (`fr`, `gb`, `de`…) | | `language` | string | auto | Result language (`en`, `fr`, `ar`…) | | `date_range` | enum | `week` | `hour` / `day` / `week` / `month` / `year` | | `max_results` | integer 1–20 | `5` | Number of pages to extract | | `scrape_pages` | boolean | `true` | Visit each URL for full content | | `concurrency` | integer 1–10 | `5` | Parallel page crawls | | `proxyConfiguration` | object | none | Apify proxy picker | *** ### Output Example ```json { "keyword": "best AI tools for marketing 2024", "title": "10 Best AI Marketing Tools to Try in 2024", "url": "https://www.example.com/ai-marketing-tools", "content_md": "## 10 Best AI Marketing Tools\n\nArtificial intelligence is transforming how marketers work...\n\n### 1. ChatGPT\nChatGPT allows marketers to generate copy, summarize reports...", "source": "post_page" } ``` | Field | Description | |---|---| | `keyword` | The search query used | | `title` | Page title as shown on Google SERP | | `url` | Full page URL | | `content_md` | Clean page content in Markdown format | | `source` | `post_page` = full page scraped / `google` = SERP snippet only | *** ### Performance | Config | Pages scraped | Estimated time | |---|---|---| | 5 results, concurrency 5 | 5 pages | ~45 sec | | 10 results, concurrency 10 | 10 pages | ~60–90 sec | | 20 results, concurrency 10 | 20 pages | ~2–3 min | # Actor input Schema ## `keyword` (type: `string`): Search query to run on Google. ## `country` (type: `string`): Google country to target. ## `language` (type: `string`): Language of the Google results. Leave empty for automatic. ## `date_range` (type: `string`): How recent results must be. ## `max_results` (type: `integer`): Maximum number of pages to scrape (1–20). ## `scrape_pages` (type: `boolean`): Visit each result URL and extract full page content as Markdown. ## `concurrency` (type: `integer`): Number of pages to scrape in parallel (1–10). ## `proxyConfiguration` (type: `object`): Optional Apify proxy (Datacenter / Residential). ## Actor input object example ```json { "country": "us", "language": "", "date_range": "week", "max_results": 5, "scrape_pages": true, "concurrency": 5 } ``` # Actor output Schema ## `results` (type: `string`): Dataset containing one item per result: keyword, title, URL, source tag, and full Markdown content. # 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("mrscrap/google-search-crawler").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("mrscrap/google-search-crawler").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 mrscrap/google-search-crawler --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=mrscrap/google-search-crawler", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Google Search Crawler", "description": "Crawl any Google search query and extract full page content as clean Markdown. Filter by country, language, and date range. Outputs title, URL, source tag, and full Markdown content for each result.", "version": "0.0", "x-build-id": "fSMx7r1kbHOYgwomJ" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/mrscrap~google-search-crawler/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-mrscrap-google-search-crawler", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/mrscrap~google-search-crawler/runs": { "post": { "operationId": "runs-sync-mrscrap-google-search-crawler", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/mrscrap~google-search-crawler/run-sync": { "post": { "operationId": "run-sync-mrscrap-google-search-crawler", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "keyword" ], "properties": { "keyword": { "title": "Keyword", "type": "string", "description": "Search query to run on Google." }, "country": { "title": "Country", "enum": [ "us", "gb", "fr", "de", "es", "it", "pt", "br", "ca", "au", "nl", "be", "ch", "at", "pl", "ru", "jp", "cn", "kr", "in", "mx", "ar", "cl", "co", "pe", "ve", "za", "ng", "eg", "ke", "gh", "ma", "dz", "tn", "sa", "ae", "tr", "il", "pk", "bd", "id", "my", "sg", "ph", "th", "vn", "nz", "ie", "dk", "se", "no", "fi", "cz", "hu", "ro", "gr", "bg", "hr", "sk", "si", "rs", "ua", "by", "lt", "lv", "ee", "lu", "mt", "cy", "is", "al", "ba", "mk", "md", "am", "ge", "az", "kz", "uz", "mn", "np", "lk", "mm", "kh", "la", "bn", "mv", "af", "iq", "ir", "jo", "kw", "lb", "ly", "om", "qa", "sy", "ye", "bh", "ps", "sd", "et", "tz", "ug", "rw", "cm", "ci", "sn", "ml", "bf", "ne", "td", "mz", "zm", "zw", "bw", "na", "ao", "cd" ], "type": "string", "description": "Google country to target.", "default": "us" }, "language": { "title": "Language", "enum": [ "", "en", "fr", "de", "es", "it", "pt", "nl", "ru", "ja", "zh-CN", "zh-TW", "ko", "ar", "hi", "tr", "pl", "sv", "da", "no", "fi", "cs", "hu", "ro", "el", "he", "id", "ms", "th", "vi", "uk", "bg", "hr", "sk", "sl", "sr", "lt", "lv", "et", "ca", "eu", "gl", "af", "sq", "hy", "az", "be", "bs", "cy", "fa", "gu", "ht", "is", "ka", "kn", "lb", "mk", "ml", "mn", "mr", "mt", "ne", "pa", "si", "sw", "ta", "te", "tl", "ur", "uz" ], "type": "string", "description": "Language of the Google results. Leave empty for automatic.", "default": "" }, "date_range": { "title": "Date range", "enum": [ "hour", "day", "week", "month", "year" ], "type": "string", "description": "How recent results must be.", "default": "week" }, "max_results": { "title": "Max results", "minimum": 1, "maximum": 20, "type": "integer", "description": "Maximum number of pages to scrape (1–20).", "default": 5 }, "scrape_pages": { "title": "Scrape page content", "type": "boolean", "description": "Visit each result URL and extract full page content as Markdown.", "default": true }, "concurrency": { "title": "Concurrency", "minimum": 1, "maximum": 10, "type": "integer", "description": "Number of pages to scrape in parallel (1–10).", "default": 5 }, "proxyConfiguration": { "title": "Proxy configuration", "type": "object", "description": "Optional Apify proxy (Datacenter / Residential)." } } }, "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 } } } } } } } } } } ```