"Information about Apple" matching MCP servers:

Provides programmatic access to Apple Voice Memos on macOS, enabling AI assistants to list, retrieve details, get audio, and transcribe recordings.

MCP server for local speech-to-text using Whisper Large V3 (MLX), enabling audio transcription with text/timestamps/SRT output and LLM-based correction, all running offline on Apple Silicon.

Analyze an hour-long YouTube video sentence by sentence in three minutes, and extract the information you need from the screen. Open-source local MCP server for AI clients.

Enhanced MCP server for sending native macOS notifications with terminal-notifier, interactive dialogs, text-to-speech, screenshots, and file selection.

Enables AI assistants to summarize, take notes on, and answer questions about YouTube, Bilibili, and Xiaohongshu videos by providing subtitles and local speech transcription with timestamps via MCP.

Enables read-first interaction with Apple Voice Memos: search transcripts, review action candidates, mark reviewed, prepare tasks for Codex, and render digests.

Enables parsing Douyin video information, downloading videos without watermark, and transcribing speech to text using Tencent Cloud ASR.

An MCP server for audio/video transcription using MLX-optimized Whisper models, offering fast performance on Apple Silicon with support for multiple output formats and batch processing.

vidlizer pulls frames out of any video, image, or PDF using ffmpeg, sends them to a vision LLM, and returns a flow array — one entry per scene. Each entry tells you what happened, who was on screen, what text was visible, and what changed. If the video has audio, it transcribes it with Apple MLX Whisper and merges the speech into each step.

Search, read, and create speech-to-text transcripts on-device with the Whisper Notes Mac app. The MCP server is built into the app (macOS, Apple Silicon) and serves over a local Unix socket — 100% offline, no open ports.

Voice interface for Claude Code enabling hands-free, conversational interaction entirely on-device for Apple Silicon Macs. It provides push-to-talk transcription and automatic spoken responses via local AI models.

Enables bidirectional voice interaction for Claude Code using local speech-to-text and text-to-speech models optimized for Apple Silicon. It provides tools to listen to user speech via microphone and speak responses aloud through system speakers.

Provides voice recognition and text extraction capabilities with support for both stdio and MCP modes, processing audio files or base64 encoded data and returning structured results with language, emotion, and speaker information.