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

MCP server that fetches YouTube video transcripts and optionally summarizes them. Supports multiple transcript formats (text, JSON, SRT, WebVTT), multi-language retrieval, and flexible YouTube URL parsing.

A Model Context Protocol (MCP) server that provides YouTube Data API v3 integration for content discovery and analytics. It enables AI assistants to search for videos, channels, playlists, and retrieve detailed metrics.

Enables AI assistants to search YouTube for videos, channels, and playlists while retrieving detailed analytics and metrics through the YouTube Data API v3. Supports advanced filtering options and provides comprehensive statistics for content discovery and analysis.

Extracts YouTube video metadata, titles, and descriptions along with transcripts generated from subtitles or OpenAI Whisper speech-to-text. This server enables users to retrieve and analyze detailed video content directly within MCP-compatible environments.

Enables AI tools to access YouTube content, including transcript extraction, video/channel info, and search.

MCP server for YouTubeTranscript.dev — extract transcripts, manage history, and power AI assistants with YouTube content.

Provides 22 read/write tools to search and retrieve YouTube videos, channels, playlists, comments, trending, and related content, and works with any MCP client.

A Model Context Protocol server that analyzes YouTube videos, enabling users to extract transcripts, generate summaries, and query video content using Gemini AI.

A small MCP server that gives agents rich context about a YouTube video — its transcript, jump-to-the-moment deep links, metadata, and most-replayed moments — so they can answer questions, summarize, pull quotes, or surface highlights.

Enables AI assistants to query YouTube search trend data, including rising topics, video keyword growth, and historical demand, using plain language.

Exposes public YouTube data — transcripts with timestamps and language listings, keyword search, video metadata and statistics, comments, channels, channel uploads, and categories — as read-only tools an LLM can call over stdio. It runs as a single local process using only a YouTube Data API key, with SQLite caching, quota tracking, and no OAuth or account access.

Allows AI agents to fetch, search, and summarize YouTube video transcripts without an API key, including chapter summaries.

Fast, minimal YouTube 'watch' engine for AI agents that extracts clean transcripts, searches, and slices any YouTube video without requiring an API key.

MCP server that provides YouTube video data to AI agents, supporting search, metadata, comments, and transcripts without an API key.

High-efficiency YouTube MCP server: Get token-optimized, structured data for your LLMs using the YouTube Data API v3.

SERP-based content scoring and optimization with 7 SEO categories.

Gives Claude access to YouTube features such as transcripts, search, video and channel stats, comments, playlists, and trending videos, with optional API key for full functionality.

Production-grade Model Context Protocol server for YouTube intelligence. Extract, analyze, and automate insights from YouTube channels and videos using the official YouTube Data API v3. Built for AI agents, automation pipelines, and content intelligence workflows.

Enables Claude Code to access YouTube features such as video transcripts, search, metadata, channel info, playlists, comments, trending videos, engagement analytics, chapters, SponsorBlock, and most-replayed heatmaps.

Enables AI models to interact with YouTube content including video details, transcripts, channel information, playlists, and search functionality through the YouTube Data API.