Yt-Dlp FAQs

Question 1

What types of video data can I extract using Yt-Dlp?

Accepted Answer

With Yt-Dlp, you can extract comprehensive video data including full transcripts (in plain text or structured JSON with optional timestamps), top comments sorted by popularity (including author, likes, and pinned status), a list of all available subtitle languages and formats, and detailed video metadata (title, channel, duration, view count, etc.).

Question 2

Which video platforms does Yt-Dlp support for data extraction?

Accepted Answer

Yt-Dlp leverages the powerful yt-dlp backend, providing extensive compatibility. It supports a vast array of platforms, including popular services like YouTube, Vimeo, and Twitch, along with thousands of other video hosting sites listed in the yt-dlp supported sites documentation.

Question 3

What is Yt-Dlp and how does it benefit AI assistants?

Accepted Answer

Yt-Dlp is an MCP server that enables AI assistants to retrieve detailed information like transcripts, comments, and metadata from online videos across thousands of sites. This significantly enhances an AI's ability to analyze and summarize video content, making it invaluable for research, content analysis, and workflow automation.

Question 4

Can I filter transcripts or comments by specific criteria?

Accepted Answer

Yes, Yt-Dlp offers filtering capabilities. For transcripts, you can specify a `start_time` and `end_time` to retrieve only relevant segments of long videos. For comments, you can set `max_comments` to fetch a desired number of top comments based on popularity, up to 500.

Question 5

Is Yt-Dlp compatible with specific AI assistant environments?

Accepted Answer

Yes, Yt-Dlp is designed as an MCP server, making it compatible with environments such as Claude Desktop and Claude Code. This allows for seamless integration into existing AI assistant workflows, empowering them with direct access to video data.

Yt-Dlp

Yt-Dlp

Key Features

Use Cases

Key Features

Use Cases