YouTube Transcript MCP Server
Enables LLMs to extract YouTube video transcripts with timestamps, metadata, and file export.
README
YouTube Transcript MCP Server
A Model Context Protocol (MCP) server that enables Large Language Models (LLMs) to extract transcripts from YouTube videos. Built with the reliable youtubei.js library, this server provides seamless transcript extraction with support for timestamps, metadata, and file exports.
✨ Features
- 🎥 Extract transcripts from any YouTube video with captions
- ⏱️ Timestamp support - Get transcripts with or without timestamps
- 📊 Rich metadata - Word count, duration, segment count, and more
- 💾 Export to files - Save transcripts as text files
- 🔧 Flexible input - Accepts full URLs, short URLs, or just video IDs
- ⚡ High reliability - Uses YouTube's internal API via youtubei.js
- 🚀 No API key required - Works out of the box
- 🛡️ Error handling - Clear, actionable error messages
📦 Installation
As an MCP Server for Claude Desktop
# Clone the repository
git clone https://github.com/tanush-yadav/youtube-transcript-mcp.git
cd youtube-transcript-mcp
# Install dependencies
npm install
As an npm Package
npm install @tanush-yadav/youtube-transcript-mcp
Or using yarn:
yarn add @tanush-yadav/youtube-transcript-mcp
🚀 Quick Start
Configuration for Claude Desktop
Add the server to your Claude Desktop configuration:
macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
Windows: %APPDATA%\Claude\claude_desktop_config.json
Linux: ~/.config/Claude/claude_desktop_config.json
{
"mcpServers": {
"youtube-transcript": {
"command": "node",
"args": ["/absolute/path/to/youtube-transcript-mcp/index.js"]
}
}
}
Or if installed globally via npm:
{
"mcpServers": {
"youtube-transcript": {
"command": "npx",
"args": ["@tanush-yadav/youtube-transcript-mcp"]
}
}
}
🛠️ Available Tools
1. get_transcript
Extract transcript from a YouTube video with optional timestamps.
Parameters:
url(string, required): YouTube video URL or video IDinclude_timestamps(boolean, optional): Include timestamps in output (default: false)
Example Request:
{
"name": "get_transcript",
"arguments": {
"url": "https://youtube.com/watch?v=dQw4w9WgXcQ",
"include_timestamps": true
}
}
Example Output with timestamps:
[00:00] We're no strangers to love
[00:04] You know the rules and so do I
[00:08] A full commitment's what I'm thinking of
2. get_transcript_with_metadata
Extract transcript along with comprehensive metadata.
Parameters:
url(string, required): YouTube video URL or video ID
Example Response:
{
"metadata": {
"video_id": "dQw4w9WgXcQ",
"video_url": "https://youtube.com/watch?v=dQw4w9WgXcQ",
"word_count": 251,
"segment_count": 42,
"duration": "3:32",
"duration_seconds": 212,
"language": "en",
"is_auto_generated": false
},
"transcript": "Never gonna give you up...",
"full_transcript_length": 1234
}
3. save_transcript
Save transcript to text file(s) on the local filesystem.
Parameters:
url(string, required): YouTube video URL or video IDfilename(string, required): Base filename (without extension)with_timestamps(boolean, optional): Save version with timestamps (default: true)
Example:
{
"name": "save_transcript",
"arguments": {
"url": "https://youtu.be/dQw4w9WgXcQ",
"filename": "rickroll_transcript",
"with_timestamps": true
}
}
Creates files:
rickroll_transcript_clean.txt- Plain text transcriptrickroll_transcript_with_timestamps.txt- Transcript with timestamps (if enabled)
💻 Programmatic Usage
As an MCP Client
import { Client } from '@modelcontextprotocol/sdk/client/index.js'
import { StdioClientTransport } from '@modelcontextprotocol/sdk/client/stdio.js'
// Initialize transport
const transport = new StdioClientTransport({
command: 'node',
args: ['/path/to/youtube-transcript-mcp/index.js'],
})
// Create client
const client = new Client({
name: 'youtube-transcript-client',
version: '1.0.0',
})
// Connect and use
await client.connect(transport)
// Get transcript with timestamps
const result = await client.callTool({
name: 'get_transcript',
arguments: {
url: 'https://www.youtube.com/watch?v=dQw4w9WgXcQ',
include_timestamps: true,
},
})
console.log(result.content[0].text)
Direct Module Usage
// Coming soon: Direct module import support
import { YouTubeTranscriptExtractor } from '@tanush-yadav/youtube-transcript-mcp'
const extractor = new YouTubeTranscriptExtractor()
const transcript = await extractor.getTranscript('dQw4w9WgXcQ')
console.log(transcript)
🌐 Supported URL Formats
The server accepts various YouTube URL formats:
- ✅ Standard:
https://www.youtube.com/watch?v=VIDEO_ID - ✅ Short:
https://youtu.be/VIDEO_ID - ✅ Embed:
https://www.youtube.com/embed/VIDEO_ID - ✅ Mobile:
https://m.youtube.com/watch?v=VIDEO_ID - ✅ Shorts:
https://www.youtube.com/shorts/VIDEO_ID - ✅ With timestamps:
https://youtube.com/watch?v=VIDEO_ID&t=123 - ✅ With playlist:
https://youtube.com/watch?v=VIDEO_ID&list=PLAYLIST_ID - ✅ Just video ID:
dQw4w9WgXcQ
📝 Usage Examples with Claude
Once configured, you can ask Claude:
"Get the transcript from https://www.youtube.com/watch?v=dQw4w9WgXcQ"
"Extract the YouTube transcript with timestamps from video ID abc123"
"Save the transcript from this video to a file: [URL]"
"Get detailed metadata and transcript from: [URL]"
"Summarize this YouTube video: [URL]" (Claude will fetch and summarize)
🔧 Development
Running Tests
npm test
Building from Source
git clone https://github.com/tanush-yadav/youtube-transcript-mcp.git
cd youtube-transcript-mcp
npm install
npm run build
Development Mode
npm run dev
Testing the MCP Server
Create a test file test-client.js:
import { Client } from '@modelcontextprotocol/sdk/client/index.js'
import { StdioClientTransport } from '@modelcontextprotocol/sdk/client/stdio.js'
const transport = new StdioClientTransport({
command: 'node',
args: ['./index.js'],
})
const client = new Client({
name: 'test-client',
version: '1.0.0',
})
await client.connect(transport)
// List available tools
const tools = await client.listTools()
console.log('Available tools:', tools)
// Test transcript extraction
const result = await client.callTool({
name: 'get_transcript',
arguments: {
url: 'https://www.youtube.com/watch?v=dQw4w9WgXcQ',
},
})
console.log('Transcript:', result.content[0].text)
await transport.close()
🐛 Troubleshooting
Common Issues
-
"No transcript available"
- ✓ Ensure the video has captions/subtitles available
- ✓ Check if the video is public and not age-restricted
- ✓ Some live streams may not have transcripts available
-
Connection errors
- ✓ Verify your internet connection
- ✓ Check if YouTube is accessible in your region
- ✓ Ensure Node.js version is 18.0 or higher
-
MCP server not found in Claude
- ✓ Verify the path in your Claude configuration is absolute
- ✓ Ensure Node.js is properly installed and in PATH
- ✓ Restart Claude Desktop after configuration changes
-
Permission errors when saving files
- ✓ Ensure write permissions in the target directory
- ✓ Check disk space availability
Debug Mode
Enable debug logging by setting the environment variable:
DEBUG=youtube-transcript-mcp node index.js
📊 Performance
- Average transcript extraction time: 1-3 seconds
- Memory usage: ~50MB
- Supports videos up to 12+ hours in length
- Handles 1000+ segments efficiently
🤝 Contributing
Contributions are welcome! Please follow these steps:
- Fork the repository
- Create a feature branch (
git checkout -b feature/amazing-feature) - Commit your changes (
git commit -m 'Add amazing feature') - Push to the branch (
git push origin feature/amazing-feature) - Open a Pull Request
Development Guidelines
- Follow existing code style
- Add tests for new features
- Update documentation as needed
- Ensure all tests pass before submitting PR
📄 License
MIT License - see LICENSE file for details
🙏 Acknowledgments
- youtubei.js - Excellent YouTube API implementation
- Model Context Protocol - MCP SDK and specification
- Anthropic - For creating Claude and the MCP protocol
📈 Roadmap
- [ ] Support for multiple language transcripts
- [ ] Batch processing for multiple videos
- [ ] Transcript translation capabilities
- [ ] Export to SRT/VTT subtitle formats
- [ ] Caching for improved performance
- [ ] Support for playlist extraction
- [ ] Real-time transcript streaming
- [ ] Custom formatting options
💬 Support
For issues, questions, or suggestions:
- 🐛 Open an issue
- 💡 Start a discussion
- 📧 Contact: tanush@cintra.run
📝 Changelog
[1.0.0] - 2024-01-03
- 🎉 Initial release
- ✨ Transcript extraction with youtubei.js
- ⏱️ Timestamp support
- 📊 Metadata extraction
- 💾 File saving capability
- 🔧 MCP protocol implementation
Made with ❤️ by the Open Source Community
Star ⭐ this repo if you find it useful!
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.