What is the YouTube MCP Server?

The YouTube MCP Server is a Model Context Protocol (MCP) server that allows AI models to interact with YouTube videos. It extracts video metadata and captions, converts them to Markdown, and provides search functionality.

What are the key features of the YouTube MCP Server?

Key features include video metadata retrieval, caption extraction (English and French), Markdown conversion with templating (Basic, Detailed, Search), flexible authentication (API key and OAuth2), and search functionality.

How does the YouTube MCP Server integrate with UBOS?

The YouTube MCP Server seamlessly integrates with the UBOS platform through the MCP protocol. It allows UBOS-based AI agents to access and process video data from YouTube.

What are the use cases for the YouTube MCP Server?

Use cases include content summarization and analysis, enhanced customer support, market research and competitive analysis, training and education, accessibility, and video SEO optimization.

What authentication methods are supported?

The server supports both API key and OAuth2 authentication. OAuth2 is required for accessing private videos.

How do I install the YouTube MCP Server?

Clone the repository, install dependencies using `npm install`, and build the project using `npm run build`.

How do I configure the server?

Create a `.env` file in the root directory with your YouTube API key and/or OAuth2 credentials. Then, add the server to your MCP settings file.

How do I use the server?

Use the provided tools to extract video info, get captions, convert to Markdown, and list available templates. Examples are in the documentation.

Can I customize the Markdown templates?

Yes, you can customize the `DEFAULT_TEMPLATES` array in `src/index.ts` to create your own Markdown templates.

What dependencies are required?

The server requires dependencies such as `@modelcontextprotocol/sdk`, `googleapis`, `google-auth-library`, `youtube-captions-scraper`, `express`, and `open`.

How do I contribute to the project?

Fork the repository, create a feature branch, commit your changes, push to the branch, and open a pull request.

Is OAuth2 required for all videos?

No, OAuth2 is only required for accessing private videos. Public videos can be accessed with an API key.

What languages are supported for caption extraction?

Currently, English and French are supported. More languages may be added in the future.

Where can I find my MCP settings file?

Typically, the file is located at ~/.config/Code/User/globalStorage/rooveterinaryinc.roo-cline/settings/cline_mcp_settings.json.

Can the YouTube MCP server be used with other services besides UBOS?

Yes, the MCP server follows the Model Context Protocol so it can be used with other services that utilize the MCP standard.

UBOS Asset Marketplace: YouTube MCP Server - Unlock Video Intelligence for Your AI Agents

Q: What is an MCP server?

MCP stands for Model Context Protocol. An MCP server acts as a bridge, facilitating communication between Large Language Models (LLMs) and external data sources or tools. It standardizes how applications provide context to LLMs.

In today’s data-rich environment, video content represents a vast, largely untapped reservoir of information. The YouTube MCP Server, now available on the UBOS Asset Marketplace, empowers you to seamlessly integrate this wealth of knowledge into your AI Agent workflows. This isn’t just about accessing video; it’s about extracting, structuring, and leveraging the insights hidden within.

What is an MCP Server, and Why Does it Matter?

Before diving into the specifics of the YouTube MCP Server, let’s clarify the fundamental concept of an MCP (Model Context Protocol) server. In essence, an MCP server acts as a bridge, facilitating communication between Large Language Models (LLMs) and external data sources or tools. It standardizes how applications provide context to LLMs, making it easier for AI agents to access and process information from diverse sources.

Think of it as a universal translator for AI. Without an MCP server, each data source would require custom integration, a time-consuming and complex process. With an MCP server, you can connect your AI agents to a wide range of resources using a consistent protocol, streamlining development and enabling more sophisticated applications.

UBOS (Universal Business Operating System) provides a full-stack AI Agent development platform. UBOS is focused on bringing AI Agents to every business department. The platform helps you orchestrate AI Agents, connect them with enterprise data, build custom AI Agents with an LLM model and Multi-Agent Systems. By integrating the YouTube MCP Server into the UBOS ecosystem, we’re unlocking a new dimension of contextual awareness for your AI agents.

Use Cases: Transforming Video into Actionable Intelligence

The applications of the YouTube MCP Server are virtually limitless, spanning a wide range of industries and use cases. Here are just a few examples:

Content Summarization and Analysis: Imagine an AI agent that can automatically summarize lengthy YouTube videos, extracting key insights and generating concise reports. This is invaluable for researchers, journalists, and anyone who needs to quickly grasp the essence of video content.
Enhanced Customer Support: Integrate the YouTube MCP Server with your customer support system to provide AI-powered assistance based on video tutorials and FAQs. Your AI agent can analyze customer queries and recommend relevant video segments, significantly improving resolution times and customer satisfaction.
Market Research and Competitive Analysis: Monitor competitor channels, analyze their video content, and identify emerging trends in your industry. The YouTube MCP Server allows your AI agent to track mentions of your brand, assess competitor strategies, and gain a competitive edge.
Training and Education: Create interactive learning experiences by integrating YouTube videos with AI-powered quizzes and assessments. The YouTube MCP Server enables you to extract captions and metadata, allowing your AI agent to generate questions, provide feedback, and personalize the learning path.
Accessibility and Inclusivity: Automatically generate transcripts and translations of YouTube videos to make content accessible to a wider audience. The YouTube MCP Server supports multiple languages, ensuring that your information reaches individuals with diverse linguistic backgrounds.
Video SEO Optimization: Analyze your own YouTube content using AI agents and the MCP Server to see which keywords are mentioned most, find gaps in your content, and then optimize your titles, descriptions, and tags for search engines using that analysis. Then you can re-upload to increase your discoverability.

Key Features: A Deep Dive into Functionality

The YouTube MCP Server boasts a comprehensive suite of features designed to streamline video data extraction and integration:

Video Metadata Retrieval: Access detailed information about YouTube videos, including title, description, upload date, author, view count, and more. This metadata provides valuable context for your AI agents, allowing them to understand the content and relevance of each video.
Comprehensive Caption Extraction: Extract both auto-generated and manually created captions from YouTube videos. The server intelligently handles different caption formats and provides accurate transcriptions, enabling your AI agents to analyze the spoken content of videos.
Multilingual Support: Seamlessly extract captions in English and French, with the potential for expanding language support in the future. This multilingual capability allows you to tap into a global pool of video content and cater to diverse audiences.
Markdown Conversion with Templating: Transform extracted captions and metadata into well-formatted Markdown documents. The server offers three built-in templates (Basic, Detailed, and Search) to suit different use cases, and allows you to customize templates to meet your specific requirements.
- Basic Template: A simple transcript format, ideal for quickly reviewing the spoken content of a video.
- Detailed Template: Includes full metadata with timestamps, providing a comprehensive overview of the video and its contents.
- Search Template: Highlights search results within the captions, making it easy to find specific information within a video.
Advanced Search Functionality: Search within video captions to pinpoint specific keywords or phrases. The server provides contextual results, highlighting the surrounding text to provide a better understanding of the search term’s meaning.
Flexible Authentication: Supports both API key and OAuth2 authentication, allowing you to access both public and private YouTube videos. OAuth2 authentication is essential for accessing restricted content, ensuring that your AI agents can access the data they need.

Getting Started: A Step-by-Step Guide

Integrating the YouTube MCP Server into your UBOS environment is a straightforward process. Here’s a quick guide to get you started:

Installation: Clone the repository, install dependencies, and build the project using standard Node.js commands.
Configuration: Create a .env file in the root directory and provide your YouTube API key and/or OAuth2 credentials. You’ll need to create a project in the Google Cloud Console and enable the YouTube Data API v3 to obtain these credentials.
MCP Integration: Add the server to your MCP settings file, specifying the command and arguments required to run the server. This step configures your UBOS environment to communicate with the YouTube MCP Server.
Usage: Utilize the provided tools to extract video info, get captions, convert to Markdown, and list available templates. The server exposes a simple API that allows you to easily access its functionality.

Customization and Extensibility

The YouTube MCP Server is designed to be highly customizable and extensible. You can modify the built-in templates, add new templates, and even extend the server’s functionality with custom code.

Custom Templates: Modify the DEFAULT_TEMPLATES array in src/index.ts to create your own Markdown templates. This allows you to tailor the output format to your specific needs.
Contributing: Contribute your own features and improvements to the project by forking the repository, creating a feature branch, and submitting a pull request.

Dependencies: The Foundation of Functionality

The YouTube MCP Server relies on a number of key dependencies to provide its functionality:

@modelcontextprotocol/sdk: Provides the core MCP functionality, enabling communication with the UBOS platform.
googleapis: The official Google APIs client library for Node.js, providing access to the YouTube Data API v3.
google-auth-library: A library for authenticating with Google APIs using OAuth2.
youtube-captions-scraper: A library for scraping captions from YouTube videos.
express: A minimalist web framework for Node.js, used to create the server’s API.
open: A library for opening URLs in the user’s default browser, used for OAuth2 authentication.

The Future of Video Intelligence

The YouTube MCP Server represents a significant step forward in the quest to unlock the intelligence hidden within video content. By seamlessly integrating with the UBOS platform, it empowers AI agents to access, analyze, and leverage video data in ways that were previously impossible.

As video content continues to proliferate, the ability to extract and understand this data will become increasingly critical. The YouTube MCP Server provides a powerful tool for businesses and organizations looking to harness the power of video intelligence and gain a competitive edge.

Ready to unlock the potential of video data? Explore the YouTube MCP Server on the UBOS Asset Marketplace today!