mcp_opendaw_split_stems
Split audio files into isolated stems (vocals, drums, bass, guitar, piano) and perform specialized separation like vocal extraction or noise cleanup using open-source models.
Instructions
Split an audio file into stems using SOTA open-source separation models.
Runs locally on GPU (GTX 1650 4GB, ~4.5 min for 4-min track). All models trained at 44100Hz — auto-resampling handled internally.
input_path: Absolute path to input audio file (WAV/MP3/FLAC/OGG). mode: Separation mode (default "bs6"): - "ensemble": Max quality, 4 passes (bass/drums/vocals/other). Slowest, best SDR. - "scnet": 4-stem (drums/bass/other/vocals). Best single-pass multi-stem. - "bs6": 6-stem (bass/drums/other/vocals/guitar/piano). Fast, low bleeding. - "polarformer": Vocal extraction only (vocals/instrumental). - "dereverb": Remove reverb from vocals (dry/reverb). - "drumsep": Drum separation (kick/snare/cymbals/toms). - "denoise": Noise cleanup for low-quality sources (clean/noise). output_dir: Directory for stem files (default: /tmp/stems_). import_to_daw: If True, load each stem into the DAW and return sample IDs for use with place_audio_region. Requires DAW bridge running.
Returns list of stem file paths (and sample IDs if import_to_daw=True).
Workflow: split_stems("track.wav", "bs6") → 6 stem WAVs split_stems("track.wav", "ensemble", import_to_daw=True) → 4 stems loaded into DAW
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| mode | No | bs6 | |
| input_path | Yes | ||
| output_dir | No | ||
| import_to_daw | No |
Output Schema
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |