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YouTube Watch Later MCP Server

MCP server for accessing YouTube Watch Later playlist

Created by rados102025/03/28
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What is YouTube Watch Later MCP Server?

what is YouTube Watch Later MCP Server? YouTube Watch Later MCP Server is a Model Context Protocol server that allows users to access their custom YouTube Watch Later playlist and retrieve URLs of videos added to it within a configured timeframe. how to use YouTube Watch Later MCP Server? To use the server, first clone the repository, install the dependencies, and build the project. You then need to create a Google Cloud project, enable the YouTube Data API, and obtain OAuth 2.0 credentials for secure access to your YouTube data. key features of YouTube Watch Later MCP Server? Retrieve video URLs added to a custom playlist within a specified number of days. Offers a simple interface that provides just the video URLs. Includes OAuth2 authentication for enhanced security. use cases of YouTube Watch Later MCP Server? Quickly accessing and sharing video links from your YouTube Watch Later playlist. Integrating with other applications to fetch video URLs programmatically. Analyzing viewing habits based on videos saved in the Watch Later playlist. FAQ from YouTube Watch Later MCP Server? How do I get the video URLs from my Watch Later playlist? Use the get_watch_later_urls tool provided by the server, specifying the daysBack parameter to filter the results. Is the server safe to use? Yes, it utilizes OAuth2 for secure access to your YouTube account, ensuring that your data remains private. Can I customize the number of days to look back? Yes, you can set the daysBack parameter to specify the timeframe for which you want to retrieve video URLs.

As an MCP (Model Context Protocol) server, YouTube Watch Later MCP Server enables AI agents to communicate effectively through standardized interfaces. The Model Context Protocol simplifies integration between different AI models and agent systems.

How to use YouTube Watch Later MCP Server

To use the server, first clone the repository, install the dependencies, and build the project. You then need to create a Google Cloud project, enable the YouTube Data API, and obtain OAuth 2.0 credentials for secure access to your YouTube data. key features of YouTube Watch Later MCP Server? Retrieve video URLs added to a custom playlist within a specified number of days. Offers a simple interface that provides just the video URLs. Includes OAuth2 authentication for enhanced security. use cases of YouTube Watch Later MCP Server? Quickly accessing and sharing video links from your YouTube Watch Later playlist. Integrating with other applications to fetch video URLs programmatically. Analyzing viewing habits based on videos saved in the Watch Later playlist. FAQ from YouTube Watch Later MCP Server? How do I get the video URLs from my Watch Later playlist? Use the get_watch_later_urls tool provided by the server, specifying the daysBack parameter to filter the results. Is the server safe to use? Yes, it utilizes OAuth2 for secure access to your YouTube account, ensuring that your data remains private. Can I customize the number of days to look back? Yes, you can set the daysBack parameter to specify the timeframe for which you want to retrieve video URLs.

Learn how to integrate this MCP server with your AI agents and leverage the Model Context Protocol for enhanced capabilities.

Use Cases for this MCP Server

  • No use cases specified.

MCP servers like YouTube Watch Later MCP Server can be used with various AI models including Claude and other language models to extend their capabilities through the Model Context Protocol.

About Model Context Protocol (MCP)

The Model Context Protocol (MCP) is a standardized way for AI agents to communicate with various services and tools. MCP servers like YouTube Watch Later MCP Server provide specific capabilities that can be accessed through a consistent interface, making it easier to build powerful AI applications with complex workflows.

Browse the MCP Directory to discover more servers and clients that can enhance your AI agents' capabilities.