@sinco-lab/mcp-youtube-transcript
v0.0.12
Published
A server built on the Model Context Protocol (MCP) that enables direct downloading of YouTube video transcripts, supporting AI and video analysis workflows.
Maintainers
Readme
MCP YouTube Transcript Server
A TypeScript Model Context Protocol server that retrieves YouTube transcripts for Claude Desktop, Cursor, Cline, Codex, and other MCP-compatible clients. It is designed for local npx usage so transcript requests are made from your own machine instead of a remote proxy.
Table of Contents
Features
Key capabilities:
- Extract transcripts from YouTube videos
- Support for multiple languages
- Android InnerTube fallback for current YouTube caption responses
- Compatible tool names:
get_transcriptsandget_transcript - Timestamped transcript output with
get_timed_transcript - Video metadata and available transcript 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
Getting Started
Prerequisites
- Node.js 18 or higher
Installation
Use a local npx configuration so transcript requests are sent from your own machine instead of a remote MCP proxy.
Create or edit the Claude Desktop configuration file:
- macOS:
~/Library/Application Support/Claude/claude_desktop_config.json - Windows:
%APPDATA%\Claude\claude_desktop_config.json
- macOS:
Add the following configuration:
{
"mcpServers": {
"youtube-transcript": {
"command": "npx",
"args": [
"-y",
"@sinco-lab/mcp-youtube-transcript"
]
}
}
}Quick setup script for macOS:
# 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"
]
}
}
}
EOLUsage
Basic Configuration
To use with Claude Desktop / Cursor / cline, ensure your configuration matches:
{
"mcpServers": {
"youtube-transcript": {
"command": "npx",
"args": ["-y", "@sinco-lab/mcp-youtube-transcript"]
}
}
}Docker
The repository includes a production Dockerfile for local container usage:
docker build -t mcp-youtube-transcript .MCP client configuration:
{
"mcpServers": {
"youtube-transcript": {
"command": "docker",
"args": ["run", "--rm", "-i", "mcp-youtube-transcript"]
}
}
}Testing
With Claude App
- Restart the Claude app after installation
- Test with a simple command:
https://www.youtube.com/watch?v=AJpK3YTTKZ4 Summarize this video
Example output:

With MCP Inspector
# 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; omit to use the best available caption track)
# enableParagraphs: false (optional)Troubleshooting and Maintenance
Checking Claude Logs
To monitor Claude's logs, you can use the following command:
tail -n 20 -f ~/Library/Logs/Claude/mcp*.logThis 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 with
mcp-server-. For example, our server's logs will be written tomcp-server-youtube-transcript.log.
Cleaning the npx Cache
If you encounter issues related to the npx cache, you can manually clean it using:
rm -rf ~/.npm/_npxThis will remove the cached packages and allow you to start fresh.
Tools
get_transcripts
Fetches transcript text from a YouTube video.
Parameters:
url(string, required): YouTube video URL or IDlang(string, optional): Language code. If omitted, the best available caption track is used.enableParagraphs(boolean, optional): Enable paragraph mode. Default:false.
get_transcript
Alias of get_transcripts for compatibility with other YouTube transcript MCP servers.
get_timed_transcript
Fetches transcript text with one timestamped line per caption segment.
Parameters:
url(string, required): YouTube video URL or IDlang(string, optional): Language code. If omitted, the best available caption track is used.
Example output:
[00:00:01.250] Hello and welcome
[00:00:03.500] Today we are going to...get_video_info
Fetches basic video metadata and available transcript languages without returning the full transcript.
Parameters:
url(string, required): YouTube video URL or ID
get_available_languages
Lists available transcript languages for a YouTube video. Use this before retrying with a specific lang value.
Parameters:
url(string, required): YouTube video URL or ID
Development
Project Structure
├── src/
│ ├── index.ts # Server entry point
│ ├── youtube.ts # YouTube transcript fetching logic
├── tests/ # Node test runner coverage
├── docs/ # Maintenance notes
├── Dockerfile # Local container build
├── dist/ # Compiled output
└── package.jsonKey Components
YouTubeTranscriptFetcher: Core transcript fetching functionalityYouTubeUtils: Text processing and utilities
Features and Capabilities
Error Handling:
- Invalid URLs/IDs
- Unavailable transcripts
- Language availability
- Network errors
- Rate limiting
- Empty caption responses caused by YouTube client enforcement
Text Processing:
- HTML entity decoding
- Punctuation normalization
- Space normalization
srv3, classic XML,json3, and VTT caption parsing- Smart paragraph detection
YouTube Access Notes
YouTube does not provide an official public API for downloading captions from arbitrary videos. This server uses YouTube's internal caption data exposed to web and Android clients. YouTube may still reject requests from some networks, hosted environments, or remote MCP providers. When that happens, the server now returns a more specific diagnostic instead of a generic No transcripts found error.
Contributing
We welcome contributions! Please feel free to submit issues and pull requests.
License
This project is licensed under the MIT License - see the LICENSE file for details.
