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shawhint/yt-mcp

Productivity workflow
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YouTube MCP server example code.

Overview

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

  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"
  1. Install dependencies:
uv sync
  1. Test the server in dev mode
uv run mcp dev main.py
  1. 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
View the full README on GitHub

Install

This server does not publish a one-line install command.

Open the repository installation guide New to MCP? Start with the mcpskill.org guide →

Configuration

{ "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" ] } } }