# YouTube Search Scraper - Mass Low-costπŸ’²πŸ”₯πŸ“ΊπŸŽ₯ (`delectable_incubator/youtube-search-scraper---mass-low-cost`) Actor Scrape YouTube search results at scale πŸ“ΊπŸŽ₯ with a powerful video scraper. Extract video titles, URLs, thumbnails, channel names, views, durations, and more metadata. Ideal for content research, keyword analysis, trend tracking, and large-scale video data collection with structured datasets πŸ“ŠπŸš€ - **URL**: https://apify.com/delectable\_incubator/youtube-search-scraper---mass-low-cost.md - **Developed by:** [Prime Scrape](https://apify.com/delectable_incubator) (community) - **Categories:** Social media, Videos, Lead generation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $0.00005 / actor start This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage. 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

Bulk Mass YouTube Scraper

--- ### πŸ“Ί Bulk Mass YouTube Scraper β­πŸ“Š The Bulk Mass YouTube Scraper is a powerful and scalable Apify Actor designed to extract structured YouTube search results at scale using multiple keywords at once. It enables video trend analysis, SEO research, competitor monitoring, content discovery, and large-scale YouTube data collection from one of the world’s largest video platforms. --- ### 🎯 What This Scraper Does Simply provide a list of YouTube search keywords and the scraper handles everything automatically. βœ… Extracts structured YouTube search results βœ… Supports multiple keywords in a single run βœ… Collects video metadata (title, views, duration, etc.) βœ… Captures channel and publication data βœ… Handles pagination automatically βœ… Normalizes view counts (text + integer) βœ… Stops at your defined maxItemsPerKeyword limit βœ… Ideal for SEO, analytics & media intelligence pipelines βœ… Ready for automation workflows βœ… Clean and structured output format --- ### πŸ“Š Data Extracted 🎬 Video Information | Field | Description | | ------------------------- | ------------------------------ | | πŸ”Ž `Search Keyword` | Keyword used to find the video | | 🎬 `Title` | Video title | | πŸ”— `Video URL` | Direct link to the video | | πŸ–ΌοΈ `Thumbnail URL` | Video thumbnail image | | πŸ“Ί `Channel` | Channel short name | | 🏷️ `Channel name` | Full channel name | | πŸ”— `Link to channel` | Channel URL | | πŸ“… `Date of publication` | Upload date | | πŸ‘οΈ `View count (text)` | Views as displayed on YouTube | | πŸ“Š `View count (integer)` | Numeric view count | | ⏱️ `Duration` | Raw duration (ISO format) | | ⏱️ `Duration label` | Human-readable duration | --- ### πŸ›  How to Use 1️⃣ Configure Input Provide one or multiple YouTube keywords: ```` { "keywords": \["AI", "ChatGPT", "Tech"], "maxItemsPerKeyword": 50 } ``` 2️⃣ Run the Actor β€’ Processes each keyword independently β€’ Scrapes YouTube search results automatically β€’ Paginates through results β€’ Extracts structured video data β€’ Stops when maxItemsPerKeyword is reached 3️⃣ Export the Dataset Download your results in multiple formats: βœ… JSON βœ… CSV βœ… Excel βœ… XML βœ… HTML --- ### βš™οΈ Input Configuration #### πŸ“₯ Input Example ``` { "keywords": \["AI tools", "machine learning", "automation"], "maxItemsPerKeyword": 100 } ``` #### Input Fields | Field | Type | Description | | -------------------- | ------- | ------------------------------- | | `keywords` | array | List of YouTube search keywords | | `maxItemsPerKeyword` | integer | Max videos per keyword | --- ### πŸ“€ Output Example ``` { "Search Keyword": "AI tools", "Title": "Top AI Tools You Should Know", "Video URL": "https://www.youtube.com/watch?v=xxxx", "Thumbnail URL": "https://i.ytimg.com/vi/xxxx/hqdefault.jpg", "Channel name": "Tech Explained", "Link to channel": "https://www.youtube.com/@techexplained", "Date of publication": "2026-01-20", "View count (text)": "125K views", "View count (integer)": 125000, "Duration": "PT12M45S", "Duration label": "12:45" } ```` --- ### πŸ“Š Output explanation | Use Case | Description | | ---------------------- | ------------------------------------ | | πŸ“Š SEO Research | Analyze keyword video performance | | πŸ”Ž Trend Discovery | Detect rising topics early | | 🎯 Competitor Tracking | Monitor channel activity | | πŸ“Ί Content Analysis | Study formats & engagement signals | | πŸ€– Automation | Build scheduled YouTube intelligence | --- ### 🌍 Why Use This Scraper? πŸš€ Extract YouTube data at scale ⚑ Multi-keyword scraping in one run πŸ“Š Clean structured datasets πŸ“Ί Ideal for SEO & content strategy πŸ“ˆ Trend detection and analytics πŸ€– Fully automation-ready --- ### ⚠️ Disclaimer This tool is an independent solution and is not affiliated with, endorsed by, or sponsored by YouTube. --- ### πŸ’Έ Pricing This scraper runs on a **pay per events subscription model**. You only pay for **successful runs**. πŸ’³ **Price:** $0.98 / 1000 results --- ### Related Actors If you're interested in other YouTube scraping solutions, explore more tools: (Coming soon) --- ### πŸ“¬ Support ⭐⭐⭐⭐⭐ Leave a 5-star rating if you like this tool --- ### 🌍 PrimeScrape Built for scalable web data extraction & automation Contact for custom scraping solutions or enterprise requests via Apify or by email. # Actor input Schema ## `keywords` (type: `array`): List of keywords to search for on YouTube ## `maxItemsPerKeyword` (type: `integer`): Maximum number of videos to collect for each keyword ## Actor input object example ```json { "keywords": [ "UK", "AI", "Nature" ], "maxItemsPerKeyword": 50 } ```` # Actor output Schema ## `overview` (type: `string`): No description # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "keywords": [ "UK", "AI", "Nature" ], "maxItemsPerKeyword": 50 }; // Run the Actor and wait for it to finish const run = await client.actor("delectable_incubator/youtube-search-scraper---mass-low-cost").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`πŸ’Ύ Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // πŸ“š Want to learn more πŸ“–? Go to β†’ 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 = { "keywords": [ "UK", "AI", "Nature", ], "maxItemsPerKeyword": 50, } # Run the Actor and wait for it to finish run = client.actor("delectable_incubator/youtube-search-scraper---mass-low-cost").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("πŸ’Ύ Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # πŸ“š Want to learn more πŸ“–? Go to β†’ https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "keywords": [ "UK", "AI", "Nature" ], "maxItemsPerKeyword": 50 }' | apify call delectable_incubator/youtube-search-scraper---mass-low-cost --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=delectable_incubator/youtube-search-scraper---mass-low-cost", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "YouTube Search Scraper - Mass Low-costπŸ’²πŸ”₯πŸ“ΊπŸŽ₯", "description": "Scrape YouTube search results at scale πŸ“ΊπŸŽ₯ with a powerful video scraper. \n\nExtract video titles, URLs, thumbnails, channel names, views, durations, and more metadata. \n\nIdeal for content research, keyword analysis, trend tracking, and large-scale video data collection with structured datasets πŸ“ŠπŸš€", "version": "0.0", "x-build-id": "qbDLMhrK6WXMslmBD" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/delectable_incubator~youtube-search-scraper---mass-low-cost/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-delectable_incubator-youtube-search-scraper---mass-low-cost", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/delectable_incubator~youtube-search-scraper---mass-low-cost/runs": { "post": { "operationId": "runs-sync-delectable_incubator-youtube-search-scraper---mass-low-cost", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/delectable_incubator~youtube-search-scraper---mass-low-cost/run-sync": { "post": { "operationId": "run-sync-delectable_incubator-youtube-search-scraper---mass-low-cost", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "keywords" ], "properties": { "keywords": { "title": "List of keywords to search for on YouTube", "type": "array", "description": "List of keywords to search for on YouTube", "items": { "type": "string" }, "default": [ "UK", "AI", "Nature" ] }, "maxItemsPerKeyword": { "title": "Max items per keyword", "type": "integer", "description": "Maximum number of videos to collect for each keyword", "default": 50 } } }, "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 } } } } } } } } } } ```