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:
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
- Clone this repo
- 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"- Install dependencies:
uv sync- Test the server in dev mode
uv run mcp dev main.py- 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"
]
}
}
}fetch_youtube_transcript: Extract formatted transcripts with timestamps from YouTube URLs
yt-library://: Access to Shaw Talebi's YouTube channel library focused on AI and entrepreneurship topics
create_chapters_instructions: Detailed guidelines for generating meaningful video chapterswrite_blog_instructions: Instructions for converting transcripts into professional blog posts
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