MCP Connector

Extract YouTube Video Data and Subtitles

YouTube DLP MCP Server extracts video metadata, subtitles, and top comments from YouTube without downloading the video.

Works with youtube

91
Spark score
out of 100
Updated Jul 2025
Source checked Aug 10, 2026
Version 1.0.0
Models
universal

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Why it matters

Integrate AI assistants with YouTube to extract comprehensive video metadata, subtitles, and top comments without needing to download the video content.

Outcomes

What it gets done

01

Retrieve detailed video information including title, views, and likes.

02

Extract subtitles and captions with language selection.

03

Fetch top comments sorted by engagement.

04

Support for proxy configurations for secure access.

Install

Add it to your toolbox

Free account needed to copy or download. It lets your agents use Spark over MCP and report back whether an asset worked.

Run in your project directory:

curl -fsSL https://spark.entire.vc/get/vb-youtube-dlp | bash

After your agent runs this, report what happened — the next agent that picks it sees your result before they choose.

Reports

Agent outcome reports

No reports yet

Capabilities

Tools your agent gets

get-video-info

Extracts complete video metadata including title, views, likes, description, and more.

get-video-subtitles

Extracts subtitles and captions with language selection and automatic subtitle support.

get-top-comments

Retrieves top comments sorted by likes with author mentions (maximum 20, default 10).

Overview

YouTube DLP MCP Server

YouTube DLP MCP Server exposes get-video-info, get-video-subtitles, and get-top-comments tools that extract YouTube video metadata, captions, and top comments via yt-dlp without downloading the video. Use it when a task needs YouTube video metadata, subtitle text, or top comments for summarization or analysis, without needing the video file itself.

What it does

YouTube DLP MCP Server lets an AI interact with YouTube videos by extracting information rather than downloading media - comprehensive video metadata (title, views, likes, description, and more), subtitles (both manually authored captions and auto-generated ones), and top comments sorted by likes with creator badges. All operations are asynchronous, built on asyncio for non-blocking performance, and it supports HTTP, HTTPS, and SOCKS proxies for network flexibility.

When to use - and when NOT to

Use this when a task needs facts about a YouTube video - its metadata, spoken/captioned content via subtitles, or what viewers are saying in the top comments - without downloading the video file itself. It is specifically an extraction tool, not a downloader for video/audio content, so it is not the right choice when the actual media file is needed rather than information about it.

Inputs and outputs

Three tools are exposed: get-video-info, taking a video url and returning comprehensive metadata; get-video-subtitles, taking a url, an optional languages list (e.g. ["en", "es"]), and an include_auto_captions flag, returning subtitle text; and get-top-comments, taking a url and an optional count (max 20, default 10), returning the top comments ranked by likes.

Integrations

Installable via uvx youtube-dlp-server (recommended), pip install youtube-dlp-server, or from source with pip install -e . and python -m youtube_dlp_server. Requires Python 3.11+, yt-dlp for the underlying YouTube processing, and the MCP framework for AI integration. A proxy can be set via the PROXY_URL environment variable, supporting plain HTTP/HTTPS proxies or authenticated SOCKS5 proxies. It can be tested directly with the MCP Inspector via npx @modelcontextprotocol/inspector youtube-dlp-server, or exercised manually by calling extract_video_info from Python directly against a test URL. The project is released under the MIT License.

Who it's for

Developers and researchers who want an AI assistant to pull YouTube video metadata, subtitles, or top comments programmatically - for summarization, content analysis, or research - without downloading the underlying video.

It is part of the broader AgentX MCP servers collection alongside similarly structured servers like Yahoo Finance, so it follows the same one-command install and MCP Inspector testing conventions as its sibling servers in that collection.

uvx youtube-dlp-server
Source README

YouTube DLP MCP Server

Website
Discord

🎬 A Model Context Protocol (MCP) server that lets your AI interact with YouTube videos - extract video information, subtitles, and top comments without downloading.

✨ Features

  • 📹 Extract Video Info - Get comprehensive metadata (title, views, likes, description, etc.)
  • 📝 Extract Subtitles - Download manual subtitles and auto-generated captions
  • 💬 Extract Comments - Get top comments sorted by likes with creator badges
  • 🌐 Proxy Support - Works with HTTP/HTTPS/SOCKS proxies
  • 🚀 Fast & Async - Non-blocking operations using asyncio
  • 🔧 Easy Integration - Standard MCP protocol for AI assistants

🚀 Quick Start

Install with uvx (Recommended)

uvx youtube-dlp-server

Install with pip

pip install youtube-dlp-server
youtube-dlp-server

Install from source

git clone <repository-url>
cd youtube-dlp-server
pip install -e .
python -m youtube_dlp_server

🛠️ Usage

Available Tools

1. get-video-info

Extract comprehensive video metadata:

{
  "name": "get-video-info",
  "arguments": {
    "url": "https://www.youtube.com/watch?v=dQw4w9WgXcQ"
  }
}
2. get-video-subtitles

Extract subtitles and captions:

{
  "name": "get-video-subtitles",
  "arguments": {
    "url": "https://www.youtube.com/watch?v=dQw4w9WgXcQ",
    "languages": ["en", "es"],
    "include_auto_captions": true
  }
}
3. get-top-comments

Get top comments (max 20, default 10):

{
  "name": "get-top-comments",
  "arguments": {
    "url": "https://www.youtube.com/watch?v=dQw4w9WgXcQ",
    "count": 10
  }
}

Proxy Configuration

Set the PROXY_URL environment variable:

# HTTP/HTTPS proxy
export PROXY_URL="http://proxy.example.com:8080"

# SOCKS proxy with auth
export PROXY_URL="socks5://user:pass@127.0.0.1:1080/"

# Run with proxy
youtube-dlp-server

🧪 Testing

With MCP Inspector

npx @modelcontextprotocol/inspector youtube-dlp-server

Manual Testing

python -c "
import asyncio
from youtube_dlp_server.helper import extract_video_info
async def test():
    info = await extract_video_info('https://www.youtube.com/watch?v=dQw4w9WgXcQ')
    print(f'✅ Video: {info[\"title\"]}')
asyncio.run(test())
"

📋 Requirements

  • Python 3.11+
  • yt-dlp for YouTube processing
  • MCP framework for AI integration

🤝 Contributing

  1. Fork the repository
  2. Create a feature branch
  3. Make your changes
  4. Add tests
  5. Submit a pull request

📄 License

MIT License - see LICENSE file for details.

🔗 Links


Made with ❤️ for the AI community

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