"youtube" matching MCP servers:

A Model Context Protocol server that enables Claude to interact with YouTube data and functionality through the Claude Desktop application.

A simple MCP server that allows AI assistants like Cursor or Claude Desktop to search for and play tracks on YouTube Music through natural language commands.

An MCP server that allows AI models to control YouTube Music playback through Google Chrome by searching and playing songs using song and artist names.

A Model Context Protocol (MCP) server that automates generating LinkedIn post drafts from YouTube videos. This server provides high-quality, editable content drafts based on YouTube video transcripts.

Enables AI agents to create and manage video compilations through n8n workflows with smart query optimization, quality analysis, batch processing, and trusted channel filtering for platforms like YouTube.

Viral-content intelligence for AI agents — 7 read-only MCP tools for TikTok/YouTube hook scoring, virality prediction, trend analysis, and viral template search, with evidence-layer scoring.

The MCP Server integrates APIs from the Youtube-Summarizer as tools within the MCP protocol, allowing for local AI application interaction and tool utilization through natural language queries.

Domain-Driven MCP server for ed-tech workflows, exposing validated MCP tools backed by LangGraph agents, Supabase document retrieval, web search, and YouTube video discovery.

Enables creators to connect their social channels so AI assistants can read their published Instagram, TikTok, YouTube, LinkedIn and Threads history, including posts, metrics, transcripts, comments and audience data, then use bundled skills to plan next posts, research creators, maintain brand docs, manage product catalogues and find outreach targets.

Enables AI agents to search, describe and call 239 social data endpoints across Instagram, TikTok, LinkedIn, Facebook, YouTube, X, Reddit, Threads and Pinterest through a single API key, covering profiles, posts, comments, followers, hashtags, ads and transcripts with one unified schema. Full responses are saved server-side and can be re-sliced for free with jq, fields or size outlines, so agents pull only the data they need into context.