"Working with Apple devices and accessing local data" matching MCP servers:

Enables chat-driven audio analysis and enhancement using local Claude, including denoising, EQ, compression, and loudness normalization, with an A/B viewer for synchronized comparison.

Enables a local, cost-controlled voice assistant for macOS that routes requests between local and Claude models, provides draft-only email and calendar access via Thunderbird and Granola with a restricted allowlist, and supports meeting follow-ups.

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

Provides local vision and audio perception for MCP-compatible agents, enabling them to read images, transcribe text from visual media, analyze videos, and convert speech to text entirely on-device. It is privacy-focused with no cloud upload or API keys by default, using Ollama for inference.

Enables MCP clients to speak by running local voice models using Chatterbox Turbo TTS or Kokoro TTS, with support for voice cloning, paralinguistic tags, and multiple voices.

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

Private, local audio and video transcription for Claude: an MCP server that runs Whisper on your computer, on the GPU or CPU, with text, SRT subtitle, or JSON output. Works with Claude Desktop, Claude Code, and claude.ai.

Enables submitting audio via URL or Base64 for local Whisper transcription, then checking job status and results or deleting transcription jobs. It provides asynchronous job handling and SSRF-protected downloads/callbacks without cloud API calls.

Enables coding agents to generate local GPU-accelerated narration audio from text, with tools for speech generation, job continuation, and model or voice queries.

A FastMCP server that exposes a locally-hosted llama.cpp LLM as MCP tools, plus utilities for weather, news, web fetching, file I/O, and more. Enables MCP-compatible clients to use a local GGUF model for text generation without external APIs.

Enables hands-free voice collaboration with a coding agent: you speak requirements aloud and hear only short, plain-language progress and completion summaries while the agent edits code, runs tests, and fixes bugs in the background. It also handles continuous speech recognition with automatic turn detection, barge-in interruption, and spoken approval prompts before risky operations.

Transcribes audio/video files to text using NVIDIA's Parakeet TDT 0.6B V2 model, with optional timestamps; also retrieves model and system hardware info.

Lets AI assistants understand what you're working on — current screen content, recent dictation, clipboard, and saved notes — running entirely on your own machine with nothing sent to the cloud.

Enables agents to inspect local videos, audio recordings, and documents by producing storyboard grids, timestamped transcripts, page images, and page-aligned text, with tools for probing media, zooming into details, locating terms, and reading subtitles. It works only with local absolute paths and does not download content or call an LLM.

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.

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

Enables MCP clients to transcribe local audio files or public audio URLs into plain text, JSON with word timestamps, or SRT/VTT subtitles, with options to save output to a file.

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.

A Windows-native MCP server that lets Claude Desktop transcribe audio files locally using whisper.cpp, with no internet connection required.

Local, private audio transcription MCP server enabling AI agents to transcribe audio files entirely on-device without uploading data.

Local speech-to-text transcription using Microsoft's VibeVoice-ASR model with speaker diarization, enabling audio transcription directly in AI tools like Claude Code, Cursor, and OpenCode.

Provides local audio transcription using whisper.cpp, supporting multiple models and audio formats. Enables transcription of audio files via MCP tools with optional timestamps.

Enables compatible local MCP hosts to inspect and control a local RVC voice-conversion engine, including listing and selecting models, setting pitch and index ratio, starting or pausing playback, and toggling original-voice bypass.

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

Enables AI to analyze audio files for loudness, voice quality, and more via the AudioLab API, supporting both public URLs and local files.

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.

Enables searching and managing local clipboard and transcription history on macOS, and provides contact resolution, profile lookup, and log-append tools for a voice-driven Android launcher while keeping data on the Mac.

Lets MCP clients such as Claude list, read, search and compare transcripts of Apple Voice Memos on macOS, keeping word-level confidence marks so uncertain words stay visibly flagged. Adds speaker separation, optional local voiceprint recognition, and independent second-reader comparisons that highlight where two engines disagreed.

Enables AI apps to transcribe local audio and video files on the user's own GPU, producing SRT/VTT subtitles and text without cloud uploads. It also helps find media files, list available devices, and list supported languages and models.