Transcribe a single audio or video file using whisper.cpp on Windows. Natively supports mp3 and wav. Automatically converts mp4, mkv, avi, mov, webm, m4a, flac, ogg etc. via FFmpeg — no manual conversion needed. Can output plain text, timestamps, JSON, or SRT subtitle files. For files that may take more than 4 minutes, set background=true to run as a detached job and use check_progress to monitor it.

Check the status of a background transcription job started with transcribe_audio (background=true). Returns current progress, elapsed time, last processed timestamp, and the transcript when complete. Call this repeatedly until the job shows as complete or failed.

Transcribe multiple audio/video files in a folder interactively, one file at a time. Shows a preview of each transcript and waits for confirmation before continuing. Saves each transcript as a .txt file next to its source. Files already transcribed (with matching .txt) are shown as done and skipped. Supported formats: mp3, wav, mp4, mkv, avi, mov, webm, m4a, flac, ogg. NOTE: For large unattended batch jobs, use whisper-cli.exe directly from the command line — see TROUBLESHOOTING.md for the command syntax.

Generate subtitle files for an audio or video file using whisper.cpp. Set language='auto' to detect the spoken language automatically. Set translate_to_english=true to also generate an English translation subtitle file. When both are requested, two .srt files are saved: one in the original language (e.g. film.ja.srt) and one English translation (film.en.srt). Load in VLC via Subtitle → Add Subtitle File. Supports all standard formats plus .3gp and .ts.

Verify whisper-cli.exe, model, and FFmpeg are all available. Run this first if anything fails.

Start an automated sequential batch transcription of all untranscribed files in a folder. Scans for files without a matching .txt, sorts by duration (shortest first), and processes them one at a time as background jobs. Each file is validated after completion — empty or suspiciously short outputs are flagged. Returns a batch ID to use with check_batch_progress.

Check the status of a batch started with start_batch. Automatically advances to the next file when the current one finishes. Returns overall progress, current file, failed files, and elapsed time. Call repeatedly until the batch shows as complete.

Analyze one or more media files using FFprobe before transcribing. For a single file: returns duration, size, codec, and estimated transcription time on CPU and GPU. For a folder: scans all supported media files and returns a sorted table with the same info for each. Use this to plan batch work, estimate how long transcription will take, or check what's already been transcribed.

Detect GPU hardware and verify Vulkan acceleration is available. Reports GPU name, VRAM, whether the Vulkan binary is installed, and recommends the best Whisper model for your hardware. Run this if you want to confirm GPU acceleration is working or diagnose why it isn't.

List all Whisper model files installed in your models directory. Shows filename, size, whether it is currently active, quantization status, and recommended use case for each model. No network calls — reads local filesystem only.

Download a Whisper model from Hugging Face directly into your models directory. Accepts a model name (e.g. large-v3-turbo, medium.en-q5_0) and handles the download automatically. Downloads only from trusted Hugging Face namespaces (ggerganov/whisper.cpp and ggml-org). After downloading, use switch_model to activate it for the current session.

Switch the active Whisper model for the current session without restarting Claude Desktop. Accepts a model filename (e.g. ggml-large-v3-turbo.bin) or full path. The model must already be installed in your models directory. Use list_models to see installed models, download_model to add new ones. Change is session-scoped — does not persist after Claude Desktop restarts.