"Tools or methods to search and analyze YouTube videos" matching MCP servers:

Provides MCP tool adapters for Bioconductor methods like limma, DESeq2, and fgsea, enabling statistical analysis of omics data through containerized R execution. It serves as a bridge between MCP clients and bioinformatics tools for reproducible research workflows.

Enables AI assistants to search YouTube videos using the official YouTube Data API v3, extract full video transcripts in multiple languages, and store/retrieve video summaries using a local database.

Enables AI assistants to search YouTube videos with rich metadata including titles, channels, view counts, and duration. Supports multi-language search and is designed for remote deployment on the Dedalus platform.

Provides AI vision analysis via OpenRouter, enabling image understanding from local paths or URLs. Supports OCR, error diagnosis, and chart/UI analysis using Gemini models.

A Model Context Protocol (MCP) server that gives AI assistants the ability to search, analyze, and extract knowledge from YouTube videos.

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 YouTube integration with Claude Code, including video search, metadata retrieval, transcript fetching, channel exploration, and trending videos.

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

Bridges YouTube API and AI assistants, enabling video analysis by downloading and processing closed captions to create summaries of YouTube videos.

Enables Claude to directly analyze YouTube channel performance by fetching real metrics such as views, watch time, retention, traffic sources, reach/CTR, and comments via YouTube APIs.

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

Enables searching for songs on YouTube and automatically playing them in a web browser using the official YouTube Data API v3. It supports cross-platform execution on Windows, macOS, and Linux with built-in input validation.

Converts any Python Click or Typer CLI into an MCP server automatically — zero-code transformation that introspects CLI commands and exposes them as MCP tools.

Enables AI assistants to search videos, read channels, browse playlists, fetch comments, and get transcripts from YouTube using the YouTube Data API v3 and InnerTube API for captions.

Enables managing a YouTube channel from Claude by listing, searching, editing, and organizing videos and playlists while retrieving channel, video, and thumbnail insights.

Enables YouTube video upload, metadata updates, thumbnail management, stats retrieval, and analytics via the YouTube Data API v3 and Analytics API using OAuth 2.0.

An MCP server that enables AI applications to search YouTube music videos and manage playlists via the YouTube Data API v3, with OAuth support for playlist and subscription management.

A lightweight MCP server for reading public YouTube data, offering tools to fetch video transcripts, playlist contents, and video metadata without requiring an API key.

Converts AI Skills (following Claude Skills format) into MCP server resources, enabling LLM applications to discover, access, and utilize self-contained skill directories through the Model Context Protocol. Provides tools to list available skills, retrieve skill details and content, and read supporting files with security protections.

Enables AI agents to read transcripts of any public video, research channels, analyze performance, read comments, and manage multiple owned channels.