"How to Get Transcripts from YouTube Videos" matching MCP servers:

Provides YouTube video transcripts as structured JSON, including timestamped captions and plain text, through the Apify YouTube Transcripts API. Supports single or batch video URLs across multiple formats.

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

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

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

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 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 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 research YouTube videos by collecting captions, comments, and channel information for analysis and comparison.

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.

An educational MCP server that wraps the Materials Project API, exposing tools to search chemical systems, get material summaries, find semiconductors by band gap, and retrieve crystal structure facts.

A keyless MCP server that lets agents search YouTube across multiple languages and queries, pull transcript highlights, ranges or query-matched passages, fetch real video frames, comments, chapters and channel outlier scores, all without an API key, OAuth or cookies. It also ships a research skill that plans multi-language queries, fans out to subagents, spot-checks quotes and reports coverage.

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.

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

Self-hosted Google Ads MCP server: 35 read tools and 10 opt-in, preview-first write tools. Maintained source relocated from getmcpads-com/google-ads-mcp-server; npm package remains @getmcpads/google-ads-mcp-server.

Self-hosted Google Analytics 4 MCP server with 27 read-only tools for the Google Analytics Data and Admin APIs. Maintained source relocated to get-mcp-ads/google-analytics-mcp-server; npm package remains @getmcpads/google-analytics-mcp-server.

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.

Enables any MCP client to score, rank, tag, and cluster user-supplied video candidates using a competitor-intelligence engine that blends velocity, outlier, engagement, and demand-gap signals into an opportunity score. It performs no fetching itself and needs no API key, so callers bring their own candidate data and receive annotated, sorted results.

A local, privacy-first MCP server providing direct access to official YouTube Data, Analytics, Reporting, and Live Streaming APIs for creators, enabling channel analysis, research, and guarded management operations.

Enables AI clients to search YouTube, fetch video transcripts, and generate transcript-grounded research briefs using MCP tools.

Enables an agent to run ten ready-made research and monitoring workflows — competitor digests, cited reports, paper alerts, market maps, regulatory and due-diligence watches — pulling from Firecrawl, Tavily, GitHub and landing results in Notion, Slack, Google Docs, Sheets and Linear. Fields are filed with the user's own keys held in the operating system keychain, and every action that creates, sends or changes anything is shown and approved first.

Converts PDF files to text for use with MCP-compatible applications like Cursor IDE.

Ask a research question; in seconds get ranked companies, vetted 10-K/10-Q passages and financials.

Give your AI the ability to find who said what with timestamps, discover what’s being discussed across videos and livestreams, and distinguish organic recommendations from sponsored ad reads.

A read-only MCP server for discovering YouTube outliers, analyzing viral Shorts, and evaluating single-video performance using stored snapshots.

Enables AI agents to search YouTube like a database, retrieve transcripts and channel data, and mine videos for claims, numbers, and demand signals — without needing an API key.

This project implements a Model Context Protocol (MCP) server providing Formula One racing data using the Python FastF1 library. Inspired by an existing TypeScript server, it offers similar F1 data functionalities natively in Python via FastF1.

Enables Claude Code to convert PDF files to high-quality PNG images, download academic papers, and batch process PDFs with automatic folder organization.

Converts Digital Object Identifiers (DOIs) to BibTeX format using the official DOI content negotiation API, enabling users to quickly generate bibliography entries for academic papers.