An MCP server designed to empower AI assistants to analyze and summarize YouTube videos by programmatically extracting captions (subtitles in multiple languages), video metadata (title, description, duration), and other relevant data. It exposes MCP commands such as get-video-info-for-summary-from-url, get-video-captions, and get-video-metadata, which return structured data that can be used to build rich video summaries. The server supports multiple YouTube URL formats, parses video IDs, and uses a caption extractor to retrieve captions in desired languages, while metadata retrieval fetches the video title, description, duration, and additional details. It can be integrated quickly via npx (no installation required) or installed globally for production deployments; MCP clients can configure the appropriate command and arguments. The MCP interface enables natural-language requests like "Can you summarize this YouTube video: URL" or "What are the main points from this video's captions?" The project is designed to work with any MCP-compatible client, delivering a structured data payload that AI assistants use to generate accurate and comprehensive summaries.