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

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

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.

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 semantic search across documentation stored in Gemini FileSearchStores, returning AI-generated answers with source citations.

Universal search engine for AI agents. Discover products, services, and businesses across every category. 10 MCP tools, zero LLM calls, millisecond responses.

The Search MCP Server enables seamless integration of network and local search capabilities in tools like Claude Desktop and Cursor, utilizing the Brave Search API for high-concurrency and asynchronous requests.

Enables natural-language search over locally indexed files such as markdown, text, images, videos, and PDFs, and retrieves indexed text or media metadata by path. It lets Cursor query a local embedding index built with Gemini and SQLite.

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.

CLI-first web and code search for agents, with MCP support for integration with IDEs like Cursor, VS Code, and Claude Code.

Enables AI agents to search local Markdown documents using natural language, with automatic indexing and section-level retrieval.

Enables searching and retrieving documentation from crawled documentation sites as an MCP server, allowing coding agents to query real docs instead of relying on training data.

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.

MCP search and evidence tool for AI agents. Rewrites queries, zooms into source domains, and returns sourced answers with metrics.

A tool that creates MCP (Model Context Protocol) servers from OpenAPI/Swagger specifications, enabling AI assistants to interact with your APIs.

MCP server for hybrid documentation search (keyword + vector) and RAG chat, enabling natural language queries with cited answers from indexed repositories.

MCP server for compressing AI embeddings by 5-7x using TurboQuant (PolarQuant + QJL), with tools to compress, decompress, estimate savings, and embed+compress vectors.

Provides hybrid search (BM25 + vector) and staleness reporting for local markdown notes, exposing search and indexing tools to AI assistants via MCP.

Free web search and page fetching for AI agents. No account or API key required. Connect to https://search.parallel.ai/mcp over Streamable HTTP. Tools: web_search and web_fetch. Free-tier rate limits apply.

Semantic, on-demand skill retrieval for Claude Code that saves tokens and improves skill discovery by replacing the native skill listing with vector embedding search.