MCP YouTube Transcript Server

by lnmunhoz

Not rated
GitHub

About

Retrieves transcripts from YouTube videos for content analysis and processing.

Details

Author
lnmunhoz
Categories
Web Scraping, Other

Option 1: Manual Configuration (Recommended for Production)

-

Create or edit the Claude Desktop configuration file:

- macOS:~/Library/Application Support/Claude/claude_desktop_config.json
- Windows:%APPDATA%\Claude\claude_desktop_config.json

{ "mcpServers": { "youtube-transcript": { "command": "npx", "args": ](#troubleshooting-and-maintenance)[ "-y", "@sinco-lab/mcp-youtube-transcript" ] } } }
# Create directory if it doesn't exist mkdir -p ~/Library/Application\ Support/Claude # Create or update config file cat > ~/Library/Application\ Support/Claude/claude_desktop_config.json << 'EOL' { "mcpServers": { "youtube-transcript": { "command": "npx", "args": [ "-y", "@sinco-lab/mcp-youtube-transcript" ] } } } EOL

Retrieves transcripts from YouTube videos for content analysis and processing.

A Model Context Protocol server that enables retrieval of transcripts from YouTube videos. This server provides direct access to video transcripts through a simple interface, making it ideal for content analysis and processing.

- Features
-
Getting Started

- Prerequisites
-
Installation

- Basic Configuration
-
Testing
-
Troubleshooting and Maintenance

- Extract transcripts from YouTube videos
- Support for multiple languages
- Format text with continuous or paragraph mode
- Retrieve video titles and metadata
- Automatic paragraph segmentation
- Text normalization and HTML entity decoding
- Robust error handling
- Timestamp and overlap detection

Option 1: Manual Configuration (Recommended for Production)

-

Create or edit the Claude Desktop configuration file:

- macOS:~/Library/Application Support/Claude/claude_desktop_config.json
- Windows:%APPDATA%\Claude\claude_desktop_config.json

{ "mcpServers": { "youtube-transcript": { "command": "npx", "args": [ "-y", "@sinco-lab/mcp-youtube-transcript" ] } } }
# Create directory if it doesn't exist mkdir -p ~/Library/Application\ Support/Claude # Create or update config file cat > ~/Library/Application\ Support/Claude/claude_desktop_config.json << 'EOL' { "mcpServers": { "youtube-transcript": { "command": "npx", "args": [ "-y", "@sinco-lab/mcp-youtube-transcript" ] } } } EOL

Option 2: Via Smithery (Development Only)

npx -y @smithery/cli install @sinco-lab/mcp-youtube-transcript --client claude

⚠️Note: This method is not recommended for production use as it relies on Smithery's proxy services.

To use with Claude Desktop / Cursor / cline, ensure your configuration matches:

{ "mcpServers": { "youtube-transcript": { "command": "npx", "args": ["-y", "@sinco-lab/mcp-youtube-transcript"] } } }

- Restart the Claude app after installation
- Test with a simple command:

https://www.youtube.com/watch?v=AJpK3YTTKZ4 Summarize this video
# Clone and setup git clone https://github.com/sinco-lab/mcp-youtube-transcript.git cd mcp-youtube-transcript npm install npm run build # Launch inspector npx @modelcontextprotocol/inspector node "dist/index.js" # Access http://localhost:6274 and try these commands: # 1. List Tools: clink List Tools # 2. Test get_transcripts with: # url: "https://www.youtube.com/watch?v=AJpK3YTTKZ4" # lang: "en" (optional) # enableParagraphs: false (optional)

To monitor Claude's logs, you can use the following command:

tail -n 20 -f ~/Library/Logs/Claude/mcp*.log

This will display the last 20 lines of the log file and continue to show new entries as they are added.

Note: Claude app automatically prefixes MCP server log files withmcp-server-. For example, our server's logs will be written tomcp-server-youtube-transcript.log.

If you encounter issues related to thenpxcache, you can manually clean it using:

This will remove the cached packages and allow you to start fresh.

Fetches transcripts from YouTube videos.

- url(string, required): YouTube video URL or ID
- lang(string, optional): Language code (default: "en")
- enableParagraphs(boolean, optional): Enable paragraph mode (default: false)

{ "content": [{ "type": "text", "text": "Video title and transcript content", "metadata": { "videoId": "video_id", "title": "video_title", "language": "transcript_language", "timestamp": "processing_time", "charCount": "character_count", "transcriptCount": "number_of_transcripts", "totalDuration": "total_duration", "paragraphsEnabled": "paragraph_mode_status" } }] }
├── src/ │ ├── index.ts # Server entry point │ ├── youtube.ts # YouTube transcript fetching logic ├── dist/ # Compiled output └── package.json

- YouTubeTranscriptFetcher: Core transcript fetching functionality
- YouTubeUtils: Text processing and utilities

- Invalid URLs/IDs
- Unavailable transcripts
- Language availability
- Network errors
- Rate limiting

- HTML entity decoding
- Punctuation normalization
- Space normalization
- Smart paragraph detection

We welcome contributions! Please feel free to submit issues and pull requests.

This project is licensed under the MIT License - see theLICENSEfile for details.

Give your AI the ability to read the web. Fetches URLs as clean markdown with 9 fallback strategies. Handles tweets, YouTube, arXiv, PDFs, and regular pages.

Extracts information from YouTube videos and channels using the YouTube Data API.

YouTube transcript API for AI agents - pay per successful transcript via x402 (USDC on Base); failed videos are never charged

Remote MCP that scrapes customer comments and reviews from Reddit, YouTube, Amazon, TikTok, app stores, and 25+ other platforms, then turns them into ad angles and customer language for marketers.

AI-powered Business Helper that analyzes thousands of YouTube videos to extract precise insights, timestamps, and actionable strategies. Instantly find the most relevant moments from podcasts, interviews, and lectures—turning long-form content into targeted business intelligence.

100% Free AI audio and video transcription with speaker diarization and YouTube support.

Turn any video — YouTube, Instagram, TikTok, Loom, direct URLs, or local files — into transcripts, key frames, OCR text, and metadata for AI agents.

Turn long videos into viral vertical shorts and publish them to TikTok, Instagram and YouTube: AI moment detection, 9:16 reframing, captions and dubbing.

YouTube growth toolkit for AI agents - research keywords, analyze channels, audit videos, pull transcripts, and more to find what works on YouTube.

AI post-production for audio and video — transcribe, summarize, find clips, cut horizontal or 9:16 vertical clips, publish to YouTube. Per-job pricing, no account.

No reviews yet — be the first

Sign in to leave a review

Use Google, GitHub, or an email account so ratings stay tied to real people.

Email sign in

No reviews posted yet.