Enable YouTube content access with MCP server for video, transcript, channel, and playlist management
The YouTube MCP Server is an essential component in integrating AI applications, particularly within the Model Context Protocol (MCP) ecosystem. It acts as a bridge between AI-driven tools and the vast repository of video content on YouTube, enabling seamless data exchange through standardized interfaces. By leveraging this server, developers can enhance their AI applications with rich multimedia capabilities, making it easier to analyze, interact with, and utilize YouTube content in various workflows.
The YouTube MCP Server offers several core features that provide extensive functionality for AI integration:
These features are implemented using MCP, a universal protocol for AI application integration, ensuring that various clients can interact seamlessly with the server's functionality via standardized commands. This setup enhances the versatility of the server in diverse use cases within the AI domain.
The YouTube MCP Server is architectured to align closely with the principles and capabilities defined by Model Context Protocol (MCP). The core architecture includes several key components:
The protocol implementation in this server focuses on efficient data transfer and streamlined process automation, which are critical for maintaining performance and responsiveness even during high load operations. By adhering to MCP guidelines, the server ensures that AI applications can leverage YouTube's vast media resources efficiently.
To begin utilizing the YouTube MCP Server in your AI workflow, follow these steps:
For a straightforward setup, you can automatically install the YouTube Server for Claude Desktop using Smithery:
npx -y @smithery/cli install @modelcontextprotocol/server-youtube --client claude
Alternatively, you can install the server manually by executing:
npm install @modelcontextprotocol/server-youtube
The YouTube MCP Server is particularly valuable for several key use cases within AI workflows:
Imagine an application where users can input a YouTube link, and the server performs real-time sentiment analysis on the video's transcript. This could be particularly useful for social impact studies or public opinion monitoring:
// Analyze video sentiment
const result = await youtube.videos.analyzeSentiment({
videoId: "video-id"
});
console.log(result.sentiments);
Create a system where users can ask questions about a YouTube video, and the server retrieves relevant information from the transcript or directly addresses the question:
// Answer user queries based on video content
const answer = await youtube.videos.getVideoInfo({
videoId: "video-id"
});
if (answer.includes("query")) {
console.log("Here is your answer.");
}
The server has been designed to be compatible with various MCP clients, ensuring broad utility across different development environments and use cases. The current compatibility includes:
MCP Client | Resources | Tools | Prompts | Status |
---|---|---|---|---|
Claude Desktop | ✅ | ✅ | ✅ | Full Support |
Continue | ✅ | ✅ | ✅ | Full Support |
Cursor | ❌ | ✅ | ❌ | Tools Only |
The YouTube MCP Server is benchmarked for both performance and compatibility to ensure that it meets the stringent requirements of AI applications. Key metrics include:
The server is tested across multiple environments and integrates well with different APIs and tools, ensuring a robust performance profile.
Configuring the YouTube MCP Server involves setting specific environment variables:
YOUTUBE_TRANSCRIPT_LANG
.{
"mcpServers": {
"youtube": {
"command": "npx",
"args": ["-y", "@modelcontextprotocol/server-youtube"],
"env": {
"YOUTUBE_API_KEY": "<YOUR_API_KEY>",
"YOUTUBE_TRANSCRIPT_LANG": "en"
}
}
}
}
Why is the YouTube API key required?
Can I change the default language for transcripts?
YOUTUBE_TRANSCRIPT_LANG
.Is there a limit on the number of video searches per minute?
How do I update the API key for my MCP client configuration?
YOUTUBE_API_KEY
environment variable in your configuration file.Can other tools besides Claude Desktop be used with this server?
Contributors to the YouTube MCP Server can refer to the CONTRIBUTING.md
file for detailed steps on setting up development environments, contributing code, and maintaining compliance with coding standards. By following these guidelines, contributors can ensure that their contributions enhance the overall quality and functionality of the server.
The YouTube MCP Server is part of a broader ecosystem designed to support developers building AI applications using Model Context Protocol (MCP). You can find additional resources and documentation at:
By participating in this community, you gain access to a network of like-minded developers and valuable resources that will aid your journey from conceptualization to deployment.
graph TD
A[AI Application] -->|MCP Client| B[MCP Protocol]
B --> C[MCP Server]
C --> D[Youtube API Wrapper]
style A fill:#e1f5fe
style C fill:#f3e5f5
style D fill:#e8f5e8
MCP Client | Resources | Tools | Prompts | Status |
---|---|---|---|---|
Claude Desktop | ✅ | ✅ | ✅ | Full Support |
Continue | ✅ | ✅ | ✅ | Full Support |
Cursor | ❌ | ✅ | ❌ | Tools Only |
This comprehensive documentation positions the YouTube MCP Server as a robust and versatile solution for integrating AI applications with YouTube content, emphasizing its value in real-world use cases and highlighting key technical elements.
RuinedFooocus is a local AI image generator and chatbot image server for seamless creative control
Learn to set up MCP Airflow Database server for efficient database interactions and querying airflow data
Simplify MySQL queries with Java-based MysqlMcpServer for easy standard input-output communication
Build stunning one-page websites track engagement create QR codes monetize content easily with Acalytica
Access NASA APIs for space data, images, asteroids, weather, and exoplanets via MCP integration
Explore CoRT MCP server for advanced self-arguing AI with multi-LLM inference and enhanced evaluation methods