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YouTube Insights MCP Server

YouTube Insights MCP Server

Local
github.com/dabidstudioMedia & Design4Updated 67w ago

About YouTube Insights MCP Server

YouTube Insights MCP Server provides transcript extraction, keyword search, and channel lookups for YouTube videos. It is suited to video discovery and channel performance analysis, and can retrieve recent uploads from a video URL.

Key features

  1. 01Extract multilingual video transcripts
  2. 02Search by keyword and retrieve video metadata
  3. 03Look up channel details and latest videos from a video URL

Use cases

  1. 01Find trending videos and review transcripts
  2. 02Analyze a channel's recent performance
  3. 03Find videos and inspect views and likes

MCP support

The MCP server exposes transcript extraction, video search, and channel lookup tools for use in agent workflows.

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

mcp.json · Universal config
{
"mcpServers": {
"youtubeinsights": {
"command": "npx",
"args": [
"-y",
"@smithery/cli"
]
}
}
}
Run commandnpx -y @smithery/cli

Local servers need a runtime on your machine (e.g. Node.js 18+). Config file locations differ by client; see your client’s docs.

Packages
npm@smithery/cli

Tools

No tool list yet

Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.

Details

From the project README

YouTube Insights MCP Server

A Model Context Protocol (MCP) server that enables insight extraction from YouTube videos, including subtitle parsing, keyword-based video discovery, and channel info retrieval.

Features

  • Extract transcripts from YouTube videos (multi-language)
  • Search videos by keyword and fetch metadata (views, likes, thumbnails, etc.)
  • Retrieve channel info and latest videos from any YouTube video URL
  • FastMCP-based server integration for easy deployment
  • MCP Tools for seamless agent workflows
Example usecases
Finding Trending Videos and Summarizing README image
Analyzing a Channel's Recent Performance README image

Installation

Installing via Smithery

To install youtubeinsights-mcp-server for Claude Desktop automatically via Smithery:

npx -y @smithery/cli install @dabidstudio/youtubeinsights-mcp-server --client claude
Using uvx (recommended)

When using uvx, no specific installation is needed.

Add the following configuration to your MCP settings file (e.g., claude_desktop_config.json for Claude Desktop):

{
  "mcpServers": {
    "youtubeinsights": {
      "command": "uvx",
      "args": ["youtubeinsights-mcp-server"],
      "env": {
        "YOUTUBE_API_KEY": "your-api-key",
      }
    }
  }
}
Development Installation
  1. Clone this repository

  2. Copy .env.example to .env and fill in your youtube data api credentials

    {
      "mcpServers": {
        "youtubeinsights": {
          "command": "uv",
          "args": [
            "--directory",
            "path/to/youtubeinsights-mcp-server",
            "run",
            "youtubeinsights-mcp-server"
          ],
          "env": {
            "YOUTUBE_API_KEY": "your-api-key",
          }
        }
      }
    }
    

Available MCP Tools

  • get_youtube_transcript: Extract full transcript (subtitles) from a YouTube video URL (supports ko, en)
  • search_youtube_videos: Search for videos on YouTube by keyword and retrieve key metadata
  • get_channel_info: Get channel metadata and recent uploads based on any YouTube video URL

Sample MCP Tool Descriptions

{
  "tool": "get_youtube_transcript",
  "description": "Extract subtitles from a given YouTube video URL."
}
{
  "tool": "search_youtube_videos",
  "description": "Search videos by keyword and return metadata including views, likes, and thumbnails."
}
{
  "tool": "get_channel_info",
  "description": "Retrieve channel info (title, subscriber count, latest uploads) based on a video URL."
}

License

This project is licensed under the MIT License. See the LICENSE file for details.

Comments

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New to MCP?

From what the protocol is to installing your first server, these answers cover most first questions.

An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.