"How to find or generate YouTube video transcripts" matching MCP servers:

Enables searching and reading local Cursor, Claude Code, and Codex session transcripts from any MCP client, with fuzzy, regex, and full-text search, plus optional semantic search.

Enables MCP clients to search locally indexed text files, PDFs, and images using natural-language descriptions, and to index folders and inspect index statistics.

Enables AI agents to generate duration-aware, fact-checked video scripts from topics or transcripts by exposing tools for live news/web research, article fetching, and transcript ingestion, plus resources and style prompt templates.

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

Enables AI assistants to search and retrieve structured video material, including dialogue, jokes, story structure, and video details through natural language queries.

An MCP server that retrieves relevant code snippets and documents to assist in generating pymilvus code, converting between ORM and client, and translating Milvus code between programming languages.

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.

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 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.

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

Enables LLMs to query documents using semantic search, supporting PDFs, Word, Excel, and more. Organizes documents by topics from folder structure and provides advanced search features like phrase matching and date filtering.

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.

Enables searching Bilibili videos by question and retrieving specific timestamped segments that answer it, with direct jump-back links. It performs local transcription, caching, and Chinese BM25 ranking to provide precise video evidence without external APIs.

A remote Model Context Protocol server that retrieves and cleans Microsoft Teams meeting transcripts via the Microsoft Graph API using delegated OAuth 2.0 authentication. It enables AI agents to discover meetings, extract speaker-attributed text, and save transcripts to SharePoint for analysis and automation.

A Cloudflare Worker that transforms Cloudflare AI Search (AutoRAG) instances into an MCP server for querying documentation. It enables AI models to search and retrieve relevant information from custom document sets stored in R2 buckets.

Exposes any SQLite database as read-only MCP tools for AI assistants, enabling listing tables, describing schemas, and running SELECT queries with filtering, ordering, and pagination.

Enables natural language search through personal video collections, returning AI-generated descriptions and direct URLs to relevant 30-second video clips.

Enables asking natural language questions about local videos, using Whisper transcription, ChromaDB vector storage, and Groq for timestamped answers via MCP.