"Fetch - Understanding its Meaning or Uses" matching MCP servers:

Enables local video inspection and offline transcription with timestamped JSON and Markdown output, enforced filesystem boundaries, and reproducible content-addressed caching.

MCP server for audio transcription using OpenRouter models, supporting verbatim, cleaned, and custom transcription modes.

Enables AI clients to transcribe YouTube links and uploaded audio or video files, then retrieve the resulting transcripts as text, SRT, VTT, or JSON with timestamps and optional speaker labels. Also supports paging through long transcripts, checking upload progress, listing or deleting jobs, and viewing remaining account minutes.

MCP server for SpeechWeave transcription, enabling AI assistants to transcribe local files and URLs via wait-first or async tools.

Enables MCP clients to fetch supported languages and limitations, assess pronunciation from audio against reference text in ten languages, and explain returned assessment results locally.

MCP server for Whipscribe — transcribe audio and video from a URL or local file via Claude Desktop, Claude Code, Cursor, Windsurf, or any MCP-compatible client.

Enables agents to submit audio files to the local Meeting Transcriber macOS app, retrieve diarized transcripts, assign speaker names, and start or stop automatic meeting detection over its localhost automation API. Everything runs on-device, so no audio or transcripts leave the Mac.

Enables an AI assistant to have its recent code actions summarized aloud through system speakers, using offline native voices or cloud neural voices. It supports asynchronous playback and voice listing so users can hear what the agent did without reading the full response.

Enables AI agents to send and verify signup OTPs, place expected outbound calls, and fetch call transcripts through the Model Context Protocol.

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.

MCP server that converts video links into AI-generated Markdown notes, with tools for task management, transcription engines, and LLM providers.

Enables local, on-device transcription of local files or URLs, returning a job ID and making transcripts, segments, and full-text search available as processing completes. Uses Whisper large-v3 with SQLite storage and stdio transport, so audio and video never leave the machine.

Enables MCP-aware agents to fetch direct captions or download audio and transcribe with local Whisper from common video platforms like YouTube, Vimeo, and Twitch.

Enables Claude to fetch the spoken text of YouTube videos from any URL or video ID, listing available captions and languages and paging through long transcripts. It also handles proxy configuration to work around YouTube IP blocks.

Provides multimedia understanding tools for LLM agents, enabling image, video, audio analysis and speech transcription via cloud-based MiMo V2.5 through OpenAI-compatible endpoints.

Enables Claude Code and Codex to directly invoke Xiaomi MiMo's full-modal capabilities including multimodal dialogue, image/video understanding, TTS, voice cloning, and ASR through MCP tools.

Local MCP server for agents to search, structure, and export authorized WhatsApp Web conversations. Uses Playwright for DOM interaction, supports message search, export, media transcription, and controlled message sending.

Enables coding agents to participate in voice calls, speaking replies while continuing their work and accepting spoken input or interruptions within the same conversation. It delivers voice input into Claude Code, Codex, Cursor, or custom HTTP endpoint workflows.

Provides multimodal understanding tools including OCR, image description, audio transcription, UI screenshot analysis, and screenshot comparison via async tools on a multimodal endpoint.

Enables supported local AI clients to control a visible desktop presence through bounded presentation tools such as animations, window control, and short local speech over a loopback endpoint, without granting decision or execution authority.