mlx-sttSpeech-To-Text with MLX (Apple Silicon) and opensource models (default GLM-ASR-Nano-2512) locally.
Install via ClawdBot CLI:
clawdbot install guoqiao/mlx-sttGrade Fair — based on market validation, documentation quality, package completeness, maintenance status, and authenticity signals.
Generated Mar 1, 2026
Researchers can transcribe interviews, lectures, or focus group recordings locally without relying on cloud services. This ensures data privacy and eliminates API costs for qualitative analysis.
Podcast creators on Apple Silicon Macs can generate accurate transcripts for episodes to create show notes, subtitles, or searchable content. Local processing avoids upload delays and subscription fees.
Journalists using MacBooks can quickly transcribe field interviews or press conferences offline, even without internet access. The tool supports various audio formats via ffmpeg conversion.
Content creators can generate captions for videos or audio content to meet accessibility standards. Running locally on macOS ensures fast processing without sharing sensitive media files externally.
Legal professionals can transcribe client meetings or deposition recordings privately on their Macs. Local execution maintains confidentiality and avoids third-party data handling risks.
Offer a free basic version with limited features, then charge for advanced capabilities like batch processing, custom vocabulary, or premium model support. Target individual creators and small teams.
Sell licenses to organizations requiring fully offline, secure transcription for sensitive audio data. Emphasize compliance with data protection regulations and Apple Silicon optimization.
Package the skill as a SDK or API for integration into other macOS applications. Charge developers for usage tiers, support, and customization services.
💬 Integration Tip
Ensure brew, ffmpeg, and uv are installed first; handle initial model download delays in your application flow.
Scored Apr 15, 2026
Transcribe audio via OpenAI Audio Transcriptions API (Whisper).
Local speech-to-text with the Whisper CLI (no API key).
ElevenLabs text-to-speech with mac-style say UX.
Local text-to-speech via sherpa-onnx (offline, no cloud)
Speak responses aloud on macOS using the built-in `say` command when user input indicates Voice Wake/voice recognition (for example, messages starting with "User talked via voice recognition on <device>").
Transcribe audio files to text using local Whisper (Docker). Use when receiving voice messages, audio files (.mp3, .m4a, .ogg, .wav, .webm), or when asked to transcribe audio content.