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qualityUses yt-dlp to download subtitles from YouTube and connects it to claude.ai via Model Context Protocol.
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MIT License
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Why this server?
Downloads subtitles from YouTube and connects it to claude.ai via Model Context Protocol, making it suitable for Cursor AI.
Why this server?
Enables AI assistants to interact with YouTube content through a standardized interface, providing tools for retrieving video information, transcripts, channel analytics, and trend analysis. It's a general purpose Youtube MCP.
Why this server?
A Model Context Protocol server for YouTube in Jp, useful if the user is looking for something specific to Japanese Youtube.
Why this server?
MCP server that enables interaction with Reddit, allowing users to read trending posts, analyze discussions, create posts, add comments, and vote on content through Claude and Cursor (Cursor AI).
Why this server?
A Model Context Protocol server that enables searching YouTube videos, retrieving and storing transcripts, and performing semantic search over video content without using the official YouTube API. Should work with Cursor given it supports MCP.
Why this server?
Allows AI assistants to access and analyze your Cursor conversation history, enabling personalized coding assistance based on your actual development patterns. Enhances cursor AI by giving more context.
Why this server?
A Model Context Protocol server that integrates with OmniFocus to enable Claude (or other MCP-compatible AI assistants) to interact with your tasks and projects. This is helpful for workflow management.
Why this server?
A Model Context Protocol (MCP) server that provides tools for searching and fetching information from Hacker News. Useful for developers.
Why this server?
A Model Context Protocol server that enables AI assistants like Claude to browse and analyze Reddit content, including searching subreddits, retrieving post details with comments, and viewing trending posts. Useful for extracting data from Reddit.
Why this server?
An MCP server implementation that provides tools for retrieving and processing documentation through vector search, enabling AI assistants to augment their responses with relevant documentation context. Useful for retrieving code examples.