# Google Videos Scraper (`codingfrontend/google-videos-scraper`) Actor Download and extract rich video metadata from Google, supporting resolutions up to 4K. Scrapes titles, duration, channel information, view counts, likes, user comments, and subtitles. Built with complete proxy rotation and anti-bot bypass support. - **URL**: https://apify.com/codingfrontend/google-videos-scraper.md - **Developed by:** [codingfrontend](https://apify.com/codingfrontend) (community) - **Categories:** Videos, Developer tools, Automation - **Stats:** 3 total users, 2 monthly users, 86.7% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $4.99 / 1,000 results This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage. 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 Videos Scraper Apify Actor that scrapes video results from Google Videos search. Extracts video title, link, source, duration, date, and thumbnail from the Google Videos SERP. ### What it does This scraper searches Google Videos and extracts structured data from the results. It supports pagination, country/language targeting, and proxy configuration for reliable access. ### Input | Field | Type | Default | Description | |-------|------|---------|-------------| | `query` | string | `"machine learning tutorial"` | The video search term to use on Google Videos | | `maxItems` | integer | `50` | Maximum number of video results to retrieve (1–500) | | `gl` | string | `"us"` | Two-letter country code for localized results (e.g. `us`, `in`, `uk`) | | `hl` | string | `"en"` | Two-letter language code (e.g. `en`, `es`, `de`) | | `proxyConfiguration` | object | Apify Residential | Proxy settings (residential recommended) | #### Example input ```json { "query": "machine learning tutorial", "maxItems": 50, "gl": "us", "hl": "en" } ```` ### Output Each result in the dataset contains the following fields: | Field | Type | Description | |-------|------|-------------| | `position` | integer | Result position on the page | | `title` | string | Video title | | `link` | string | Direct URL to the video | | `source` | string | Video source / channel name | | `duration` | string | Video duration (e.g. "12:34") | | `date` | string | Published date or relative age (e.g. "2 months ago") | | `thumbnail` | string | Thumbnail image URL | | `searchQuery` | string | The original search query | | `searchUrl` | string | Google Videos search URL used | | `scrapedAt` | string | ISO timestamp of when the result was scraped | #### Example output ```json { "position": 1, "title": "Machine Learning Full Course - Learn Machine Learning 10 Hours", "link": "https://www.youtube.com/watch?v=GwIo3gDZCVQ", "source": "edureka!", "duration": "10:33:49", "date": "5 years ago", "thumbnail": "https://i.ytimg.com/vi/GwIo3gDZCVQ/hq720.jpg", "searchQuery": "machine learning tutorial", "searchUrl": "https://www.google.com/search?q=machine+learning+tutorial&tbm=vid&start=0&gl=us&hl=en", "scrapedAt": "2026-02-28T08:30:00.000Z" } ``` ### Features - Scrapes video results from the Google Videos tab - Extracts title, link, source, duration, date, and thumbnail - Handles Google consent pages and CAPTCHA detection - Session rotation and browser fingerprint randomization - Parallel tab scraping for fast pagination - Configurable country and language targeting - Residential proxy support for reliable access # Actor input Schema ## `query` (type: `string`): The video search term to use on Google Videos ## `maxItems` (type: `integer`): Maximum number of video results to retrieve ## `gl` (type: `string`): Two-letter country code for localized Google results (e.g. 'us', 'in', 'uk') ## `hl` (type: `string`): Two-letter language code for Google interface language (e.g. 'en', 'es', 'de') ## `proxyConfiguration` (type: `object`): Proxy settings for the scraper. Residential proxies are recommended for Google. ## Actor input object example ```json { "query": "machine learning tutorial", "maxItems": 50, "gl": "us", "hl": "en", "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } } ``` # 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 = { "query": "machine learning tutorial", "maxItems": 50, "gl": "us", "hl": "en", "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } }; // Run the Actor and wait for it to finish const run = await client.actor("codingfrontend/google-videos-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 = { "query": "machine learning tutorial", "maxItems": 50, "gl": "us", "hl": "en", "proxyConfiguration": { "useApifyProxy": True, "apifyProxyGroups": ["RESIDENTIAL"], }, } # Run the Actor and wait for it to finish run = client.actor("codingfrontend/google-videos-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 '{ "query": "machine learning tutorial", "maxItems": 50, "gl": "us", "hl": "en", "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } }' | apify call codingfrontend/google-videos-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=codingfrontend/google-videos-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Google Videos Scraper", "description": "Download and extract rich video metadata from Google, supporting resolutions up to 4K. Scrapes titles, duration, channel information, view counts, likes, user comments, and subtitles. Built with complete proxy rotation and anti-bot bypass support.", "version": "0.0", "x-build-id": "tVlVWDj7Z1LLt6hDS" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/codingfrontend~google-videos-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-codingfrontend-google-videos-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/codingfrontend~google-videos-scraper/runs": { "post": { "operationId": "runs-sync-codingfrontend-google-videos-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/codingfrontend~google-videos-scraper/run-sync": { "post": { "operationId": "run-sync-codingfrontend-google-videos-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "query" ], "properties": { "query": { "title": "Search Query", "type": "string", "description": "The video search term to use on Google Videos", "default": "machine learning tutorial" }, "maxItems": { "title": "Maximum Items", "minimum": 1, "maximum": 500, "type": "integer", "description": "Maximum number of video results to retrieve", "default": 50 }, "gl": { "title": "Google Country", "type": "string", "description": "Two-letter country code for localized Google results (e.g. 'us', 'in', 'uk')", "default": "us" }, "hl": { "title": "Language", "type": "string", "description": "Two-letter language code for Google interface language (e.g. 'en', 'es', 'de')", "default": "en" }, "proxyConfiguration": { "title": "Proxy Configuration", "type": "object", "description": "Proxy settings for the scraper. Residential proxies are recommended for Google.", "default": { "useApifyProxy": true, "apifyProxyGroups": [ "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 } } } } } } } } } } ```