
shawhint/yt-mcp
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YouTube MCP server example code.
개요
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. 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 1. Clone this repo 2. Install uv if you haven't already 4. Add server config to AI app (e.g. Claude Desktop or Cursor). - : Extract formatted transcripts with timestamps from YouTube URLs - : Access to Shaw Talebi's YouTube channel library focused on AI and entrepreneurship topics - : Detailed guidelines for generating meaningful video chapters - : Instructions for converting transcripts into professional blog posts
README
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:
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
- 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"
]
}
}
}
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 chapterswrite_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
설치
This server does not publish a one-line install command.
Open the repository installation guide MCP 초보자라면? mcpskill.org 가이드부터 시작하세요 →설정
{
"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"
]
}
}
}