"Using YouTube to obtain and summarize video content" matching MCP servers:

A hosted Model Context Protocol server providing read-only YouTube tools for search, video/channel data, and transcripts, with no Google Cloud project or API key required.

Enables AI assistants to access YouTube organic analytics, including channel stats, video performance, watch time, and audience engagement, via the YouTube Data API v3 and Analytics API v2.

Enables AI agents to analyze YouTube channels and identify videos that significantly outperform the channel's median view count, along with channel search, video lookup, and trending tools.

Enables AI agents to search videos, retrieve metadata and transcripts, pinpoint exact moments via hybrid semantic search, and conduct multi-video research with timestamp deep links—all without YouTube API keys.

Enables competitor content analysis by scraping pages, extracting keywords, identifying content gaps, comparing headings, scoring readability and quality, checking SERP features, and clustering competitors.

Enables read-only research on YouTube by exposing video metadata, transcripts, comments, search, channels, playlists, and trending data through four task-oriented tools.

Enables AI assistants to analyze YouTube channels, videos, transcripts, and content strategy through structured tool calls.

Enables Codex to retrieve YouTube video dossiers, compare videos, access channel performance and retention curves, save analysis reports, and manage experiments through a stateless MCP endpoint.

Provides MCP tools for fetching timestamped YouTube transcripts and top comments, scanning spreadsheets for video links, and a local web UI for grounded video summaries.

Enables turning YouTube video URLs into timestamped, citation-ready transcript evidence, with optional search, comments, analytics, and cross-video comparison for MCP clients.

Evidence-first YouTube research server enabling search, transcript citation, video analysis, flashcards, and collateral generation for MCP hosts and VS Code.

A specialized MCP server for Claude Desktop that enhances AI-assisted medical learning by fetching and processing educational resources from PubMed, NCBI Bookshelf, and user-provided documents.

A specialized Model Context Protocol server that enhances AI-assisted medical learning by connecting Claude Desktop to PubMed, NCBI Bookshelf, and user documents for searching, retrieving, and analyzing medical education content.

Combines Naver DataLab trends, blog/news search, translation, and Unsplash images into a single research pipeline for content creators. Generates comprehensive research reports from a single query.

Enables AI agents to generate duration-aware, fact-checked video scripts from topics or transcripts by exposing tools for live news/web research, article fetching, and transcript ingestion, plus resources and style prompt templates.

Enables researching YouTube channels and videos by listing uploads, reading transcripts, extracting frames, and searching, without needing a YouTube API key.

MCP server for extracting structured intelligence from YouTube channels and videos — transcripts, topics, and competitive signals for AI-powered research workflows.

An MCP server for researching YouTube niches. It searches videos, fetches metadata, calculates engagement metrics, downloads thumbnails, and produces aggregate niche statistics for analysis.

Enables AI clients to browse instruments, items, dimensions, expert assignments, and calculate Content Validity Index (CVI) via a standard MCP interface.

Enables AI assistants to research YouTube videos by collecting captions, comments, and channel information for analysis and comparison.