Question 1

What is the YouTube MCP Server?

Accepted Answer

The YouTube MCP Server is a Model Context Protocol (MCP) server implementation that allows AI language models to interact with YouTube content through a standardized interface.

Question 2

What is MCP?

Accepted Answer

MCP (Model Context Protocol) is an open protocol that standardizes how applications provide context to LLMs. It acts as a bridge, allowing AI models to access and interact with external data sources and tools.

Question 3

What key features does the YouTube MCP Server offer?

Accepted Answer

The server provides video information retrieval, transcript/caption management, channel analysis, and trend analysis, allowing AI agents to understand video content, analyze engagement, track trending topics, access transcripts, and monitor channel performance.

Question 4

What tools are available within the YouTube MCP Server?

Accepted Answer

The server includes tools like `getVideoDetails`, `searchVideos`, `getTranscripts`, `getRelatedVideos`, `getChannelStatistics`, `getChannelTopVideos`, `getVideoEngagementRatio`, `getTrendingVideos`, and `compareVideos`.

Question 5

How do I install the YouTube MCP Server?

Accepted Answer

You can install it automatically via Smithery or manually using npm or Git. The automatic installation command is `npx -y @smithery/cli install @icraft2170/youtube-data-mcp-server --client claude`.

Question 6

What environment variables do I need to configure?

Accepted Answer

You need to set the `YOUTUBE_API_KEY` with your YouTube Data API key and optionally `YOUTUBE_TRANSCRIPT_LANG` for the default caption language.

Question 7

How do I get a YouTube Data API key?

Accepted Answer

You need to access Google Cloud Console, create a new project or select an existing one, enable YouTube Data API v3, and create API credentials (API key).

Question 8

What is UBOS, and how does it relate to the YouTube MCP Server?

Accepted Answer

UBOS is a full-stack AI Agent Development Platform that simplifies the process of orchestrating AI agents, connecting them with enterprise data, and building custom AI agents. It integrates seamlessly with the YouTube MCP Server.

Question 9

What are some use cases for the YouTube MCP Server?

Accepted Answer

Use cases include marketing and advertising, market research, education and training, content creation, and media monitoring, enabling AI agents to optimize campaigns, gauge consumer sentiment, curate content, generate ideas, and track online reputation.

Question 10

What are the system requirements for the YouTube MCP Server?

Accepted Answer

The server requires Node.js 18.0.0 or higher.

YouTube Data Server

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