YouTube Transcript MCP

The YouTube Transcript MCP is a practical tool designed to pull written text directly from YouTube videos. Instead of having to watch a long video or manually transcribe its content, this server allows an AI to "read" exactly what was said. By simply providing a video link or ID, the tool retrieves the captions or subtitles, making it easy to summarize long presentations, find specific quotes, or translate video dialogue into different languages without leaving the chat interface. Beneath its simple interface, the server provides a robust tool called `get_transcript` that handles various URL formats and video identifiers. It offers significant flexibility by allowing users to specify language codes, such as English or Korean, ensuring the AI captures the correct subtitle track. The system is built with resilience in mind, featuring sophisticated error handling for scenarios like private videos, missing transcripts, or network interruptions, which ensures a reliable connection between the video platform and the AI. For developers building AI-powered workflows, this MCP server serves as a critical bridge that converts unstructured video data into clean, structured text that large language models (LLMs) can process efficiently. It can be easily integrated into Claude Desktop or other MCP-compatible clients via Smithery or a simple JSON configuration. This enables complex automated tasks, such as generating markdown documentation from video tutorials, performing sentiment analysis across video series, or creating searchable databases from video-based educational content.

Category: Design, Media & Creative

Tags: captions, subtitles, transcription, video, youtube

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How to install and configure YouTube Transcript MCP

1. Installation Via Smithery (Automatic for Claude Desktop): bash npx -y @smithery/cli install @kimtaeyoon83/mcp-server-youtube-transcript --client claude Via mcp-get: shell npx @michaellatman/mcp-get@latest install @kimtaeyoon83/mcp-server-youtube-transcript Manual Development Setup: 1. Install dependencies: npm install 2. Build the server: npm run build ---

2. Configuration To use the YouTube Transcript server with Claude Desktop or other MCP clients, add the following configuration to your settings file: json { "mcpServers": { "youtube-transcript": { "command": "npx", "args": ["-y", "@kimtaeyoon83/mcp-server-youtube-transcript"] } } } ---

3. Available Tools * get_transcript * Description: Extract transcripts from YouTube videos. * Parameters: * url (string, required): YouTube video URL or video ID. * lang (string, optional, default: "en"): Language code for transcript (e.g., 'en', 'ko'). ---

4. Example Prompts You can use the following patterns when interacting with an LLM equipped with this tool: * "Extract subtitles from this video: https://youtu.be/ODaHJzOyVCQ" * "Get the transcript for the YouTube video with ID VIDEO_ID in English." * "Please provide the Korean transcript for this URL: https://www.youtube.com/watch?v=VIDEO_ID"

What you can do with YouTube Transcript MCP

Use Case 1: Automated Video Summarization for Long-Form Content Problem: Users often need to digest information from long-form YouTube content like 2-hour podcasts, university lectures, or recorded webinars, but they lack the time to watch the video in its entirety. Solution: This MCP allows an AI assistant to fetch the full text of the video instantly. The AI can then process the entire transcript to generate concise summaries, bulleted key takeaways, or a table of contents with timestamps. Example: A user provides a link to a long Lex Fridman podcast and asks: "Summarize the key arguments made by the guest regarding AI safety in this video: [URL]."

Use Case 2: Transforming Video Tutorials into Written Documentation Problem: Developers and DIY enthusiasts often find it easier to follow written step-by-step guides than pausing and rewinding a video tutorial. Manually transcribing these steps is tedious. Solution: By using the get_transcript tool, the AI can pull the instructional dialogue and technical steps. It can then format this raw text into structured Markdown documentation, complete with code blocks and headings. Example: "Fetch the transcript for this React tutorial [URL] and turn it into a step-by-step technical blog post with clear instructions."

Use Case 3: Content Repurposing for Social Media Problem: Content creators need to distribute their video content across multiple platforms (like Twitter

X, LinkedIn, or Newsletters), but rewriting video scripts into short-form text takes significant manual effort. Solution: The MCP retrieves the video's spoken content, which the LLM can then rewrite into different formats—such as a viral Twitter thread, a professional LinkedIn post, or a newsletter blurb—while maintaining the original voice of the creator. Example: "Extract the transcript from my latest YouTube upload [URL] and draft 5 engaging tweets highlighting the most controversial points discussed."

Use Case 4: Multi-Language Research and Translation Problem: Researchers often need to access information from foreign-language news reports or interviews on YouTube, but auto-generated translations in the video player can be clunky or hard to analyze as a whole. Solution: Users can specify the lang parameter to retrieve transcripts in the original language. The LLM can then perform a high-quality translation or provide a cross-lingual analysis of the content. Example: "Get the Korean transcript for this tech review [URL] and translate the specific criticisms of the hardware into English for my market research report."

Use Case 5: Deep Search and Fact-Checking Problem: Finding a…

Key facts

  • Open Source
  • Design, Media & Creative, Web Search & Research
  • captions, subtitles, transcription, video, youtube

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