

Extract public YouTube video data in bulk via video IDs, including title, description, channel info, views, likes, comments and duration. Export structured data to CSV or JSON with one click for content analysis and statistics.
YouTube Scraper is a data extraction tool designed to batch collect video title, description, channel info, view count, likes, comments, duration, and other data from public YouTube videos via video ID. Using CoreClaw, you can obtain structured data with zero coding, helping with content analysis and data statistics.
| 🎬 Video Title and ID | 🔗 Video Link |
| 🖼️ Video Thumbnail | 👀 Video View Count |
| 👍 Video Likes | 💬 Comment Count |
| 🕐 Video Duration | 📅 Release Time |
| 👤 Channel Name | 🔗 Channel Link |
CoreClaw YouTube Scraper handles proxy rotation, task scheduling, data standardization, and final delivery for you in the background. In just a few minutes, you can obtain data through the following steps:
Enter YouTube video ID.
Example: 8RePenzQH80
For your convenience, output results are displayed in tables and tabs. You can choose to download results in CSV/JSON format. Here is an example of video data scraped using video ID:
If you need to scrape other types of data, CoreClaw offers the following professional toolsets optimized for different scraping scenarios.
The tool will scrape complete public data from the video, including video title, ID, link, thumbnail, view count, release date, likes, release location, channel name, channel link, subscriber count, video duration, comments, video description, links in description, subtitles, monetization status, comment settings, etc.
The tool supports detailed error feedback and intelligent retry mechanisms. When scraping anomalies occur, the service will return a response containing error codes and detailed prompt information. For temporary errors, the service defaults to automatic retry.
Video data is very suitable for content analysis applications:
Yes. Supports batch input of multiple video IDs to scrape complete data from multiple videos at once, facilitating batch analysis and data integration.
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