ShawhinT/yt-mcp

YouTube MCP Server

A Model Context Protocol (MCP) server that provides tools and prompts for working with (Shaw Talebi's) YouTube videos, including transcript extraction, chapter generation, and blog post creation.

Prepared for AgentCon 2025 - Dallas workshop.

Resources:

• Recording
• Slides

Overview

This MCP server enables AI assistants to:

• Extract timestamped transcripts from YouTube videos
• Access a curated library of AI and entrepreneurship videos
• Generate structured video chapters from transcripts
• Convert video transcripts into engaging blog posts
• Get table of Shaw Talebi's YouTube videos as of June 25, 2025

How to run this example

1. Clone this repo
2. Install uv if you haven't already

# Mac/Linux
curl -LsSf https://astral.sh/uv/install.sh | sh

# Windows
powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"

2. Install dependencies:

uv sync

3. Test the server in dev mode

uv run mcp dev main.py

4. Add server config to AI app (e.g. Claude Desktop or Cursor).

{
  "mcpServers": {
    "YT-MCP": {
      "command": "/Users/shawhin/.local/bin/uv", # replace with global path to your uv installation
      "args": [
        "--directory",
        "/Users/shawhin/Documents/repos/yt-mcp/", # replace with global path to repo
        "run",
        "main.py"
      ]
    }
  }
}

Features

🛠️ Tools

• fetch_youtube_transcript: Extract formatted transcripts with timestamps from YouTube URLs

📚 Resources

• yt-library://: Access to Shaw Talebi's YouTube channel library focused on AI and entrepreneurship topics

📝 Prompts

• create_chapters_instructions: Detailed guidelines for generating meaningful video chapters
• write_blog_instructions: Instructions for converting transcripts into professional blog posts

Project Structure

yt-mcp/
├── main.py                    # MCP server implementation
├── prompts/
│   ├── create_chapters.md     # Chapter generation guidelines
│   └── write_blog.md         # Blog writing instructions
├── resources/
│   └── videos.csv            # Video library database
├── yt-mcp-example.ipynb      # Usage examples
├── pyproject.toml            # Project configuration
└── requirements.txt          # Dependencies