Viral Shorts

MCP-powered YouTube Shorts discovery tool for finding viral videos using natural language in Claude Desktop

中文文档

Features

• 🔥 Discover trending Shorts

• 📊 Analyze viral potential

• 🎯 Track trending topics

• 🔍 Find niche trends

• 📝 Summarize video stories

Tech Stack: YouTube Data API v3 • VPH (Views Per Hour) • Engagement Rate • MCP Protocol

Quick Start

Prerequisites

• Python 3.11+ (optional, uvx auto-manages)

• YouTube Data API Key

• Claude Desktop or MCP client

1. Get YouTube API Key

1. Visit Google Cloud Console

2. Create a new project

3. Enable YouTube Data API v3

4. Create API Key

5. (Recommended) Restrict key to YouTube Data API v3 only

2. Configure Claude Desktop

Edit Claude Desktop config:

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

Add:

{
  "mcpServers": {
    "viral-shorts": {
      "command": "uvx",
      "args": ["--from", "youtube-shorts-viral-agent", "shorts-server"],
      "env": {
        "YOUTUBE_API_KEY": "your-api-key-here"
      }
    }
  }
}

Note:

• Replace your-api-key-here with your actual API key

• uvx auto-downloads from PyPI

• No manual installation needed

3. Start Using

1. Restart Claude Desktop completely

2. Use natural language:

Find trending AI Shorts from the last 24 hours

Usage Examples

Example 1: Discover Trends

Show me viral AI Shorts from the last 24 hours

Returns Markdown table with:

• Title, Channel, Views, VPH, Engagement Rate, Viral Score, Age

Example 2: Analyze Video

Analyze this video's potential: https://www.youtube.com/shorts/abc123

Example 3: Find Topics

What's trending in tech category?

Example 4: Custom Parameters

Find programming Shorts from last 12 hours with 500k+ views

Claude auto-extracts:

• Keyword: "programming"

• Time range: 12 hours

• Min views: 500,000

Available Tools

1. get_youtube_shorts_trends

Discover trending YouTube Shorts.

Parameters:

• keyword (string): Search keyword, empty for global trends

• hours_ago (int): Time range in hours, default 24

• max_results (int): Result count, default 10

• min_views (int): Min view threshold, default 100,000

• search_by_tag (boolean): Search by exact tag match, default false

2. analyze_video_potential

Deep analysis of a single video.

Parameters:

• video_url (string): YouTube Shorts URL

3. get_trending_topics

Find trending topics.

Parameters:

• category (string): tech/entertainment/education/gaming/all

• hours_ago (int): Time range, default 24

4. summarize_video_story

Extract video story and core content.

Parameters:

• video_url (string): YouTube Shorts URL

5. discover_niche_trends

Find niche viral trends within a topic.

Parameters:

• main_topic (string): Main keyword (e.g., "AI", "tutorial")

• hours_ago (int): Time range, default 24

• min_videos (int): Min videos per niche, default 3

• top_niches (int): Top N niches to return, default 10

Core Metrics

VPH (Views Per Hour)

• Formula: Total Views ÷ Hours Since Published

• Meaning: Growth velocity

• Thresholds:

  • ≥ 10,000: 🔥 Super viral

  • ≥ 5,000: ⭐ High potential

  • ≥ 1,000: ✨ Potential

Engagement Rate

• Formula: (Likes + Comments) ÷ Views × 100

• Meaning: Content quality

• Thresholds:

  • 10%: Excellent

  • 5%: Good

  • 2%: Average

Viral Score

• Formula: VPH × Time Weight × (1 + Engagement Boost)

• Meaning: Comprehensive ranking score

• Features:

  • Newer videos weighted higher

  • High engagement significantly boosts score

API Quota Management

YouTube Data API v3 Quota

• Default: 10,000 units/day

• Reset: Daily at Pacific Time midnight

Cost Breakdown

Best Practices

• Keep max_results ≤ 10 per search

• Limit to ~50 calls/day

• Use min_views to filter results

• Use view count for overall popularity

• Use VPH for fast-growing new videos

Project Structure

viral-shorts/
├── .env.example            # MCP config example
├── .gitignore              # Git ignore rules
├── LICENSE                 # MIT License
├── README.md               # English documentation
├── README.zh.md            # Chinese documentation
├── MCP_EXPLAINED.md        # MCP protocol explained
├── pyproject.toml          # PyPI config
├── uv.lock                 # Dependency lock
├── src/
│   ├── server.py           # MCP Server (annotated)
│   ├── youtube/
│   │   ├── client.py       # YouTube API client
│   │   └── analyzer.py     # Viral analysis
│   ├── models/
│   │   └── video.py        # Data models
│   └── utils/
│       └── config.py       # Config (env vars)
└── tests/
    └── test_youtube.py     # Unit tests

FAQ

Q: "YOUTUBE_API_KEY not set" error

1. Check claude_desktop_config.json has env.YOUTUBE_API_KEY set

2. Ensure no extra spaces or quotes in API key

3. Fully restart Claude Desktop

Q: "API quota exhausted" error

1. Wait for quota reset (Pacific Time midnight)

2. Request quota increase in Google Cloud Console

3. Reduce search frequency or lower max_results

Q: Claude can't find tools

1. Verify claude_desktop_config.json format is correct

2. Fully restart Claude Desktop

3. Check Claude Desktop logs for errors

Q: No search results

1. Expand time range (e.g., 12h → 24h)

2. Use broader keywords

3. Lower min_views threshold

Tech Stack

• Python: 3.11+

• MCP: FastMCP 2.13.1+

• API: google-api-python-client 2.187.0+

• Validation: Pydantic 2.12.4+

License

MIT License - see LICENSE

Links

• GitHub: https://github.com/Xeron2000/viral-shorts

• MCP Docs: https://modelcontextprotocol.io/

• FastMCP: https://github.com/jlowin/fastmcp

Start discovering viral videos with natural language! 🚀