YouTube Data

This YouTube Data MCP server serves as a powerful digital bridge that allows AI models to "see" and understand what is happening on YouTube. In its simplest form, it gives an AI the ability to read video titles, descriptions, and full transcripts. This means a language model can summarize a hour-long tutorial, find specific information buried inside a lecture, or explain a video's content to a user without anyone having to manually watch the footage or copy-paste text. Beyond simple summaries, the tool provides a comprehensive suite of analytical features for deeper content exploration. It can perform targeted keyword searches, retrieve detailed channel statistics like subscriber counts and growth metrics, and even identify trending videos based on specific regions or categories. It also features robust multi-language caption support, allowing AI agents to process and translate global content with precision while maintaining time-stamped references for exact context. For developers building LLM-integrated systems, this server implements the Model Context Protocol to offer a standardized interface powered by the YouTube Data API v3. It includes specialized tools for engagement ratio calculations and multi-video comparisons, which are essential for sentiment analysis or automated market research. By integrating these capabilities, developers can transform an AI from a static text processor into a dynamic researcher capable of extracting structured insights, tracking channel performance, and navigating the vast landscape of public video data in real time.

Category: Data & Analytics

Tags: analytics, search, transcripts, video, youtube

Visit YouTube Data

How to install and configure YouTube Data

1. Installation Automatic Installation via Smithery You can automatically install the YouTube MCP Server for Claude Desktop using the following command: `bash npx -y @smithery/cli install @icraft2170/youtube-data-mcp-server --client claude` Manual Installation You can install via npm: `bash npm install youtube-data-mcp-server` Or by cloning the repository: `bash git clone https://github.com/icraft2170/youtube-data-mcp-server.git cd youtube-data-mcp-server npm install` ---

2. Configuration YouTube API Setup 1. Access the Google Cloud Console. 2. Create a new project or select an existing one. 3. Enable the YouTube Data API v3. 4. Create API credentials to generate an API key. MCP Client Configuration (Claude Desktop) Add the following JSON to your Claude Desktop configuration file: `json { "mcpServers": { "youtube": { "command": "npx", "args": ["-y", "youtube-data-mcp-server"], "env": { "YOUTUBE_API_KEY": "YOUR_API_KEY_HERE", "YOUTUBE_TRANSCRIPT_LANG": "ko" } } } }` Environment Variables - `YOUTUBE_API_KEY`: Your YouTube Data API key (Required). - `YOUTUBE_TRANSCRIPT_LANG`: Default caption language (Optional, default: 'ko'). ---

3. Available Tools | Tool Name | Description | Required Parameters | | --- | --- | --- | | `getVideoDetails` | Get detailed information about multiple YouTube videos including metadata, statistics, and content details | `videoIds` (array) | | `searchVideos` | Search for videos based on a query string | `query`, `maxResults` (optional) | | `getTranscripts` | Retrieve transcripts for multiple videos | `videoIds` (array), `lang` (optional) | | `getRelatedVideos` | Get videos related to a specific video | `videoId`, `maxResults` (optional) | | `getChannelStatistics` | Retrieve metrics for multiple channels (subscribers, views, etc.) | `channelIds` (array) | | `getChannelTopVideos` | Get the most viewed videos from a specific channel | `channelId`, `maxResults` (optional) | | `getVideoEngagementRatio` | Calculate engagement metrics (views, likes, comments, and ratio) | `videoIds` (array) | | `getTrendingVideos` | Get currently popular videos by region and category | `regionCode` (optional), `categoryId` (optional) | | `compareVideos` | Compare statistics across multiple videos | `videoIds` (array) | ---

4. Example Prompts While no specific example prompts were listed in the content, the tools enable the following interactions: - "Search for the top 5 trending videos in the United States." - "Get the transcript for the video with ID [VIDEO_ID] and summarize it." - "Compare the engagement ratios of these three YouTube channels." - "Find videos related to [VIDEO_ID] and show their view counts."

What you can do with YouTube Data

Use Case 1: Automated Video Summarization and Knowledge Extraction Problem: Researchers and students often need to extract key information from long educational videos, lectures, or webinars without spending hours watching the entire content. Solution: This MCP allows an AI assistant to fetch the full transcript of a specific video using `getTranscripts`. The AI can then process the text to generate concise summaries, bulleted key takeaways, or even answer specific questions about the video's content using time-stamped references. Example: A user provides a URL for a 2-hour coding tutorial. The AI uses `getTranscripts`, analyzes the text, and provides a timestamped table of contents and a summary of the specific libraries used in the video.

Use Case 2: Competitor Benchmarking and Content Strategy Problem: Content creators and digital marketers struggle to manually track which topics are performing best for their competitors or within their specific niche. Solution: By using `getChannelTopVideos` and `getVideoEngagementRatio`, users can identify exactly which videos have the highest "stickiness" (likes

comments relative to views) rather than just looking at raw view counts. Example: A tech reviewer asks the AI to "Analyze the top 5 videos from [Competitor Channel] from the last month." The AI uses the MCP to pull the data, calculates the engagement ratios, and identifies that "Comparison" videos are outperforming "Unboxing" videos for that specific audience.

Use Case 3: Regional Market Research and Trend Analysis Problem: Marketing teams launching products in new international markets need to know what content is currently capturing the public's attention in specific regions. Solution: The `getTrendingVideos` tool allows users to filter by `regionCode` and `categoryId`. This provides a real-time snapshot of popular culture and viral content in specific locales. Example: A fashion brand wants to launch in South Korea. They ask the AI to "Show me the top 10 trending videos in the 'Entertainment' category in South Korea." The AI retrieves the list, describes the common themes, and helps the brand align its local marketing message with current trends.

Use Case 4: AI-Powered "Watch List" Curation Problem: When researching a complex new topic (like "Quantum Computing" or "Sustainable Farming"), users are often overwhelmed by search results and don't know which videos are actually authoritative or relevant. Solution: The AI can use `searchVideos` to find initial results and then use `getRelatedVideos` and `compareVideos` to filter for the most relevant, highly-rated, and statistically significant content. Example: A user says, "I want…

Key facts

Part of MCP Servers

Related MCP servers

MCP KQL Server — Execute KQL queries using Azure authentication. Requires Azure CLI login.
MCP Jupyter Complete — A server for Jupyter notebook manipulation with position-based operations and VS Code integration.
MCP MD2PDF Server — Convert Markdown documents to PDF with support for Mermaid diagrams.
MCP Media Processing Server — A server for media processing, offering powerful video and image manipulation using FFmpeg and ImageMagick.
MCP Music Analysis — Analyze audio from local files, YouTube, or direct links using librosa.
MCP OCR Server — An MCP server for Optical Character Recognition (OCR) using the Tesseract engine.