What are the primary use cases for YouTube Captions?

Its primary use cases include providing comprehensive video content to AI systems for summarization, analysis, or translation, especially when integrated with MCP hosts like Cursor or Claude Code, or directly via its REST API.

What kind of subtitles and languages does it support?

It supports both official and auto-generated subtitles, available across a multitude of languages. You can retrieve them as cleaned plain text transcripts or in raw SRT/VTT formats, catering to various use cases.

How does YouTube Captions handle large video transcripts?

YouTube Captions features robust pagination, allowing it to safely fetch and deliver even very large transcripts in manageable chunks. If a response is truncated, it provides a 'next_cursor' for fetching subsequent parts.

Is it easy to deploy and use in a production environment?

Yes, it boasts a Docker-first design for easy local and remote deployment via Docker Hub or docker-compose. For production HTTP deployments, it includes optional authentication and allowlists for enhanced security.

What is YouTube Captions?

YouTube Captions is an MCP (Multi-Tool Communication Protocol) server powered by yt-dlp that fetches paginated transcripts and raw subtitles from YouTube videos. It's designed for seamless integration with AI tools and MCP hosts like Cursor and Claude Code.

YouTube Captions

Name: YouTube Captions
Author: samson-art

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Fetches YouTube transcripts and subtitles using yt-dlp, providing paginated responses for integration with MCP hosts.

YouTube Captions

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Fetches YouTube transcripts and subtitles using yt-dlp, providing paginated responses for integration with MCP hosts.

This tool acts as an MCP server, facilitating the retrieval of YouTube video transcripts and raw subtitles. It leverages yt-dlp to access caption data, offering both plain text and structured SRT/VTT formats. Designed with flexibility in mind, it supports communication over stdio for local applications like Cursor, and HTTP/SSE for remote deployments, including via Docker. Its pagination feature ensures seamless handling of extensive transcripts, making it ideal for large-scale data processing or integration with AI assistants and other applications that require structured access to YouTube content.

主要功能

01Fetches cleaned plain text transcripts or raw SRT/VTT subtitles

02Supports official and auto-generated subtitles across multiple languages

03Provides pagination for safely handling large responses

04Includes optional authentication and allowlists for production HTTP deployments

050 GitHub stars

06Docker-first design for easy local and remote deployment

使用案例

01Enable AI assistants (e.g., Cursor, Claude Code) to summarize YouTube videos

02Integrate YouTube caption fetching into custom development workflows

03Provide subtitles for data analysis or content creation applications

YouTube Captions

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YouTube Captions

主要功能

使用案例

Neon

Figma Context

Magic

Diagram Maker & Visualizer

GH Issues Auto-Fixer

Discord Integration

主要功能

使用案例