"YouTube" matching MCP servers:

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

Transforms YouTube into a queryable knowledge source with search, video details, transcript analysis, and AI-powered tools for summaries, learning paths, and knowledge graphs. Features quota-aware API access with caching and optional OpenAI/Anthropic integration for advanced content analysis.

Enables semantic search across thousands of indexed educational YouTube videos covering topics like engineering, marketing, and strategy. It allows users to query insights from top creators directly through Claude Code using the Model Context Protocol.

A Model Context Protocol server that enables searching YouTube videos, retrieving and storing transcripts, and performing semantic search over video content without using the official YouTube API.

Builds a searchable knowledge base from YouTube video transcripts with hybrid semantic and keyword search. Allows LLM assistants to search, organize, and retrieve timestamped information from videos you've watched.

This read-only MCP Server allows you to connect to YouTube Analytics data from Claude Desktop through CData JDBC Drivers. Free (beta) read/write servers available at https://www.cdata.com/solutions/mcp

Generates production-ready short video scripts from real-time web search data using Tavily and Gemini, exposed as MCP tools.

Extract YouTube transcripts for AI agents, RAG pipelines, and LLM workflows. Supports any YouTube URL. Returns clean text or timestamped segments. No API keys required.

Enables building a local, searchable knowledge base from YouTube videos, with research, transcript retrieval, and timestamped citations.

An MCP server for SearchApi that provides Google web, news, scholar, and YouTube search as agent-ready MCP tools.

Enables AI assistants to search and retrieve transcripts from the Entra.Chat podcast about Microsoft Entra ID, with timestamped YouTube links and guest information.

Unifies YouTube transcripts, YouTube search, and Google NotebookLM into a research pipeline for Claude Desktop and MCP clients.

Enables LLMs to perform web searches through Perplexica with multiple focus modes (web, academic, YouTube, Reddit) and optimization settings, returning AI-generated responses with source citations.

A server that provides access to Google Gemini AI capabilities including text generation, image analysis, YouTube video analysis, and web search functionality through the MCP protocol.

A controllable multi-source search MCP server for AI agents. Enables searching multiple sources like Reddit, X, YouTube, and more, with control over sources, time window, and optional synthesis.

Enables interaction with Google NotebookLM to create notebooks, add sources (PDF, URL, YouTube), and ask questions with citations.

MCP server for turning YouTube channels into a queryable local knowledge base. Enables BM25 search and extractive Q&A over captions with timestamped citations.

Enables AI-powered searches through a local Perplexica instance with multiple focus modes including web search, academic search, YouTube, Reddit, and more, with streaming support and conversation history.

An MCP knowledge server that enables saving and retrieving memory across sessions, with tools to ingest text, URLs, YouTube, and files, and perform semantic search.

Integrates with SerpAPI and YouTube to provide comprehensive search capabilities across Google Search, News, Scholar, Trends, Finance, Maps, Images, YouTube, and transcript retrieval for AI assistants.

A research MCP server that enables AI agents to query the internet using multiple sources like SearXNG, GitHub, Reddit, and YouTube, and returns synthesized answers with citations.

Pay-per-success YouTube transcript extractor for AI agents and RAG pipelines. Timestamps, SRT, plain text. Failed videos are never charged. $0.005/video.

A semantic search MCP server for YouTube transcripts using OpenAI embeddings and ChromaDB, enabling natural language queries to find conceptually similar content beyond keyword matching.

Answers queries based on Alex Hormozi's YouTube content using local RAG with SQLite and vector embeddings.

Fetches YouTube transcripts and enables semantic search within them using local embeddings, allowing an LLM to retrieve relevant passages with timestamps.

Four utilities in one server: PDF text, ruled tables and OCR from a URL as pages, documents or RAG chunks; YouTube thumbnail URLs and files with per-size availability; sports scores, schedules and standings across 33 leagues; and ATP/WTA tennis with per-set scores and draws.

MCP server for querying your local Google Takeout activity (Search/YouTube history) via SQLite/FTS5. Provides tools for keyword search, activity stats, and database info, enabling AI assistants to cite your personal history.

Federated, local-first search for AI agents: one query fans across transcripts, files, a knowledge graph, a vector store, the live web, and YouTube, fused by trust-weighted RRF into one ranked answer. Five modes (grep/lexical/semantic/hybrid/rerank), runs entirely on your machine over MCP.

Turn YouTube, TikTok, X videos and websites into structured data. Skip the hassle of video transcription and data scraping. Our APIs help you build better software and AI products faster.

RAG MCP server for PDFs, YouTube, GitHub repos, and Discord exports. Index documents and query with citations via LangChain and Chroma.