YouTube MCP Server: Transcript Harvesting & AI Summaries

Fuel your AI with YouTube gold! Our MCP Server scrapes transcripts, hands 'em to LLMs for instant summaries, blog magic, and beyond – no API grind, just pure video wisdom." )

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About YouTube MCP Server

What is YouTube MCP Server: Transcript Harvesting & AI Summaries?

This server acts as a middleware solution enabling AI language models to access and analyze YouTube video content. By extracting transcripts from video URLs, it bridges the gap between unstructured video data and structured text inputs required by AI systems. The tool empowers models to reference, summarize, and discuss video content within conversational workflows.

How to use YouTube MCP Server: Transcript Harvesting & AI Summaries?

Install the uv package manager via platform-specific commands
Clone the repository using git clone and setup virtual environment
Register the server with uv run mcp install command
Initiate transcript analysis directly through compatible AI platforms like Claude Desktop by providing YouTube URLs

YouTube MCP Server Features

Key Features of YouTube MCP Server: Transcript Harvesting & AI Summaries?

Automated transcript extraction and formatting
Direct integration with AI language models via MCP protocol
Support for end-to-end video analysis workflows
Platform-agnostic implementation (Mac/Linux/Windows)
User-configurable transcript processing pipelines

Use cases of YouTube MCP Server: Transcript Harvesting & AI Summaries?

Common applications include:

Automated video content summarization for time-constrained users
Academic research requiring scalable video text analysis
Educational platforms needing transcript-based study materials
Content moderation systems requiring text-based analysis of video libraries
Chatbot implementations needing real-time video context reference

YouTube MCP Server FAQ

FAQ from YouTube MCP Server: Transcript Harvesting & AI Summaries?

Does it work with all YouTube videos?
Requires videos with publicly available transcripts. Members-only or geo-restricted content may cause extraction failures.

How are transcripts processed?
Uses YouTube's API for initial extraction, then applies normalization and formatting for optimal AI model compatibility.

Can I customize the analysis pipeline?
Yes - developers can modify the server's processing logic in server.py to add NLP preprocessing steps.

What AI platforms are supported?
Designed for MCP protocol compatibility, currently tested with Claude Desktop. Adaptable for other LLM platforms through API adjustments.

Content

YouTube MCP(Model Context Protcol) Server

This MCP server provides a tool to fetch and extract transcripts from YouTube videos. It enables AI language models (LLMs) to:

Access complete text transcripts from YouTube video URLs
Process and analyze video content through transcripts
Reference and discuss video information in conversations

The server acts as a bridge between AI models and YouTube content by automatically extracting and formatting video transcripts.

Instead of saying can't access links

Setup

Install uv (Python package manager):

Mac:

    brew install uv

Linux:

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

Windows:

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

Clone this repository:

git clone [email protected]:PrajwalPrashanth/youtube-mcp-server.git

cd youtube-mcp-server

Create a virtual environment and install dependencies:

uv venv

source .venv/bin/activate  
# On Windows: .venv\Scripts\activate
uv pip install -r pyproject.toml

Add this MCP server to Claude Desktop (download)

uv run mcp install -e . server.py -n "youtube-mcp"

Once this is done you should see the tool icon in the UI

and you can ask for it to do actions (like summarize) with the transcript by providing a YT video