Youtube Content Management MCP
Y

Youtube Content Management MCP

An MCP server based on the YouTube Data API v3, providing search and data analysis functions for videos, channels, and playlists, supporting content discovery and indicator query.
2 points
8.1K

What is the YouTube Content Management MCP Server?

This is a tool specifically designed for AI assistants, allowing AI to directly access YouTube data. It's like equipping AI with the ability to search and analyze YouTube. You can use natural language to ask AI to find videos, analyze channel data, and view playlist content without manually operating the YouTube website.

How to use this service?

First, you need to obtain a YouTube API key. Then, configure this MCP server in your AI assistant (such as Claude Desktop or VSCode). After the configuration is complete, you can directly ask questions to the AI. For example, 'Find me the most popular Python tutorial videos in the last month', and the AI will use this tool to search and return the results.

Applicable scenarios

Suitable for content creators, market researchers, educators, data analysts, and other people who need to quickly obtain YouTube information. You can use it to: 1. Research the performance of competitors' channels 2. Find popular videos on specific topics 3. Analyze the viewing data trends of videos 4. Discover high - quality content creators in related fields 5. Collect video resources for teaching or research

Main Features

๐ŸŽฅ Intelligent Video Search
Search for YouTube videos using natural language. Support sorting by relevance, date, rating, and views. You can filter video duration and publication time. The search results will display key indicators such as the number of views, likes, and comments.
๐Ÿ“บ Channel Discovery and Analysis
Search for YouTube channels and obtain detailed data, including the number of subscribers, the total number of videos, and the total number of views. Help you quickly find high - quality content creators in specific fields.
๐Ÿ“‹ Playlist Search
Find playlists on specific topics and learn about the number of videos in the playlist and the total number of views. Suitable for finding systematic learning resources or thematic content.
๐Ÿ“Š Video Data Analysis
Get detailed statistical data of a single video, including the number of views, likes, and comments. Help analyze the performance of the video and user interaction.
๐Ÿ“ˆ Channel Performance Analysis
View the overall performance data of a YouTube channel, including the current number of subscribers, the total number of views, and the number of uploaded videos. Used for channel research and competitive analysis.
๐Ÿ“‘ Playlist Statistics
Get detailed information about the playlist, including the number of videos and the total number of views of all videos. Evaluate the content quality and popularity of the playlist.
Advantages
๐Ÿค– Natural Language Interaction: Describe your needs directly in Chinese or English without learning complex search syntax
๐Ÿ“Š Rich Data: In addition to basic information, you can also obtain key indicators such as the number of views, likes, and subscriptions
โšก Fast and Efficient: The AI assistant can process multiple queries at once, faster than manual search
๐Ÿ” Advanced Filtering: Support multi - dimensional filtering by time, sorting method, video duration, etc.
๐Ÿ”„ Real - Time Data: The data obtained is the latest data from YouTube, ensuring the timeliness of information
Limitations
๐Ÿ”‘ Requires an API Key: You must apply for a YouTube API key and configure it correctly
๐Ÿ“ˆ Has Usage Limits: The YouTube API has a daily call limit (default 10,000 times)
๐Ÿ’ป Requires Technical Configuration: You need to correctly configure the MCP server in the AI assistant
๐Ÿ“ฑ Depends on the Network: Requires a stable network connection to access the YouTube API
๐ŸŽฏ Search Accuracy: The quality of search results is affected by the YouTube search algorithm

How to Use

Obtain a YouTube API Key
Visit the Google Cloud Console, create a project and enable the YouTube Data API v3, then generate an API key. It is recommended to set API restrictions to only allow access to the YouTube Data API.
Install Dependencies
Ensure that Python 3.8 or a higher version is installed, and then install the necessary Python packages. You can use pip or uv for installation.
Configure the AI Assistant
According to the AI assistant you are using (Claude Desktop or VSCode), add the MCP server settings to the configuration file. You need to specify the Python path and the API key.
Start Using
Restart the AI assistant, and then you can ask questions in natural language. The AI will automatically recognize the situations where the YouTube tool needs to be used and call the corresponding functions.

Usage Examples

Case 1: Content Research and Analysis
As a content creator, you want to study the performance of your competitors' videos and understand which types of videos are more popular.
Case 2: Teaching Resource Collection
A teacher needs to prepare teaching materials for Python programming courses and wants to find systematic learning resources.
Case 3: Market Trend Analysis
A market analyst needs to understand the content trends and popular creators in a certain field.
Case 4: Single Content Analysis
You want to understand the performance of a specific video and analyze its user interaction data.

Frequently Asked Questions

Do I need to pay to use this service?
Why can't I use my API key?
What should I do if the search results show 'Quota has been used up'?
Can I search for Chinese content?
Can this tool obtain real - time viewing data of videos?
Do I need programming knowledge to use this tool?
Is this tool safe? Will my API key be leaked?
Why do some videos not have the number of likes or comments?

Related Resources

YouTube Data API Official Documentation
The complete technical documentation of the YouTube Data API v3, including detailed descriptions of all API endpoints
Google Cloud Console
The platform for applying for and managing YouTube API keys, where you can view API usage and quotas
MCP Protocol Documentation
The official specification document of the Model Context Protocol, to understand the working principle of MCP
Python Google API Client Library
A Python client library for accessing Google APIs (including the YouTube API)
Pydantic Documentation
The documentation of the Python data validation library. This tool uses Pydantic for input validation

Installation

Copy the following command to your Client for configuration
{
  "mcpServers": {
    "youtube-content-management": {
      "command": "python",
      "args": ["/path/to/youtube-content-management-mcp/main.py"],
      "env": {
        "YOUTUBE_API_KEY": "your_youtube_api_key_here"
      }
    }
  }
}
Note: Your key is sensitive information, do not share it with anyone.

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