YouTube MCP Server
by PrajwalPrashanth
This MCP server fetches and extracts transcripts from YouTube videos, enabling AI language models (LLMs) to access and analyze video content. It acts as a bridge between AI models and YouTube content by automatically extracting and formatting video transcripts.
Last updated: N/A
What is YouTube MCP Server?
The YouTube MCP Server is a tool that extracts transcripts from YouTube videos and makes them accessible to AI language models. It allows LLMs to process, analyze, and reference video content through its transcripts.
How to use YouTube MCP Server?
To use the server, first install uv, clone the repository, create a virtual environment, and install dependencies. Then, add the MCP server to Claude Desktop using the provided command. Once installed, you can provide a YouTube video URL and ask the AI to perform actions (like summarize) using the transcript.
Key features of YouTube MCP Server
Extracts transcripts from YouTube videos
Formats transcripts for AI models
Provides a bridge between YouTube and AI
Allows LLMs to analyze video content
Integrates with Claude Desktop
Use cases of YouTube MCP Server
Summarizing YouTube videos with AI
Analyzing video content for research
Referencing video information in AI conversations
Creating AI-powered video content analysis tools
FAQ from YouTube MCP Server
What is an MCP server?
What is an MCP server?
MCP stands for Model Context Protocol. It's a way for AI models to access external tools and data.
What is uv?
What is uv?
uv is a fast, modern Python package manager and resolver.
How do I install the server?
How do I install the server?
Follow the setup instructions in the README, including installing uv, cloning the repository, and installing dependencies.
How do I add the server to Claude Desktop?
How do I add the server to Claude Desktop?
Use the command uv run mcp install -e . server.py -n "youtube-mcp".
What kind of actions can I perform with the transcript?
What kind of actions can I perform with the transcript?
You can ask the AI to summarize the video, analyze the content, or answer questions based on the transcript.