"A platform for managing YouTube channel content and analytics" matching MCP servers:

Fetches YouTube transcripts and metadata (title, channel, duration) for URLs, using subtitles or on-device Whisper STT when no subtitles are available, enabling chat-based YouTube video analysis.

YouTube MCP by SocialDataX for video search and details, comments and replies, channel profiles and uploads or Shorts, and speech-to-text transcripts.

Enables an AI client to obtain the text of a YouTube video by returning its metadata, the captions YouTube already provides, or a Whisper transcription run on a local GPU. Text responses are bounded and pageable, and long transcriptions run as background jobs that survive request timeouts.

Enables intelligent transcription of YouTube videos with automatic optimization for any video length, using local OpenAI Whisper processing and speaker diarization.

This MCP server fetches and extracts transcripts from YouTube videos, enabling AI language models to access and analyze video content.

An MCP server for content creation that extracts video transcripts, scrapes web articles, and performs web searches.

Self-host a realtime voice-call companion for coding agents. Exposes an MCP endpoint that agents can poll as an alternate input stream.

MCP server providing tools to fetch YouTube video transcripts with metadata, supporting direct YouTube transcripts and audio transcription via multiple backends (whisper, AssemblyAI, OpenAI, Gemini).

Enables MCP clients and agents to fetch YouTube transcripts and caption lists from video IDs or links, preferring manual/auto captions by ordered language preference and falling back to local Faster-Whisper audio transcription when captions are unavailable. Results include source, language, full text and timestamped segments, with CLI exports to JSON, text, SRT and WebVTT, all without paid APIs or API keys.

Transcribe YouTube videos for LLM chat applications. Supports fetching transcripts in multiple languages and includes an ad-removal instruction.

Remote MCP server that enables Claude AI to extract transcripts from YouTube videos with zero setup, supporting multiple languages and all URL formats.

Enables voice assistants to find nearby service providers, connect users to live video representatives for natural conversation, and handle appointment booking. It also returns confirmed bookings so the assistant can add them to its calendar.

A multi-agent human-computer interaction system that enables natural interaction through integrated visual recognition, speech recognition, and speech synthesis capabilities.

Enables MCP clients such as Claude Code, Codex and Cursor to retrieve timestamped transcripts of public YouTube videos, either from cache, from native captions, or via asynchronous audio-generation jobs that are polled by job ID. It returns the source URL, selected language and millisecond-offset segments without summarizing the video itself.

Downloads YouTube audio and transcribes it locally using faster-whisper, saving transcripts as Markdown and JSON files for Obsidian and Hermes ingestion.

Enables AI models like Claude to easily access and utilize subtitle data from YouTube videos by extracting transcripts from video URLs with support for multiple languages.

A Model Context Protocol (MCP) server that allows AI assistants like Claude to control real smart bulbs via UDP network communication, featuring voice commands, AI reasoning, and direct hardware control.

Enables MCP-capable chat clients to synthesize speech from text, convert it with a local RVC voice model, and render the result in an inline audio player.

Enables extracting timestamped transcripts from YouTube and TikTok URLs, including title, channel, and duration, via a single tool.

Turns a YouTube link into a readable, timestamped Markdown transcript by preferring existing subtitles and falling back to local Whisper transcription, with optional Traditional-to-Simplified Chinese conversion and Obsidian-friendly output.