"Instructions for installation or setting up something" matching MCP servers:

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

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

Transcribe audio/video URLs and detect silence for cutting, with pay-per-call billing in USDC via x402, no account or API key required.

Enables local text-to-speech synthesis for Claude and Cursor using Supertonic 3, with support for multiple voices, expressions, and languages. No API key or cloud required.

Voice input for Claude Code — speak Vietnamese or English; hold a hotkey, speak, release, and the transcribed text is cleaned and pasted into the input box for editing before sending.

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 MCP-capable assistants to transcribe local audio files or URLs and perform speaker diarization for Spanish and Portuguese audio, with options for speaker count hints, domain prompts, and transcript retrieval in multiple formats.

Enables high-quality transcription and subtitle generation from local media files or URLs using Faster Whisper on local hardware. It supports automatic language detection and integration with MCP clients for seamless speech-to-text workflows.

An MCP server for audio-to-text transcription using Google's Gemini API via OpenRouter, offering multiple tools for raw, cleaned, or formatted transcripts with support for local and remote deployment.

MCP server integrating VolcEngine for automatic speech recognition (ASR) and text-to-speech (TTS), converting audio to text or text to audio files.

Enables AI agents on macOS to securely read and search the local Messages database, catch up on missed messages via a persistent inbox, and send texts or files to allowlisted chats, with optional voice note transcription and text-to-speech.

MCP server for audio transcription using local faster-whisper or OpenAI Whisper API, enabling multilingual transcription with optional GPT post-processing.

Enables AI assistants to transcribe audio files from URLs or local paths using AssemblyAI's services, with support for speaker diarization, language detection, and asynchronous job management through a standardized MCP interface.

MCP server that turns any audio or video source into structured, searchable intelligence for agents, enabling download, transcription, semantic search, speaker identification, and more.

Lets cloud-based coding agents send progress updates and read messages that a macOS voice app speaks aloud and accepts spoken replies for, with no installation on the agent side. Agents can report status, fetch instructions dictated by voice, and acknowledge them through a hosted endpoint.

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.

Lets AI agents search, read and export call recordings, transcripts and AI meeting notes from Digisensus Recorder, a free open-source call recorder for macOS, and start or stop recording. Runs locally on the Mac and talks to the app over a Unix socket.

Transcribe public videos and audio (YouTube, TikTok, Instagram, Facebook, Pinterest, Google Drive) into accurate, timestamped text from Claude, ChatGPT, Cursor or any MCP client. Spanish, English and dozens of languages auto-detected. Poll-based (transcription takes minutes), same free-beta limits as the app. Docs: https://justtranscribe.ai/mcp

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.

Provides voice summaries after each AI request in Cursor, Cline, or any MCP-supported editor, allowing users to hear what was done and stay informed without staring at the screen.