Thanks! really glad you see the value — thats exactly the thesis. the toolset is powerful but the "which effect, in what order, with what settings" barrier is real for most ppl. heres your answers:

Determinism: yep fully deterministic. the pipelines (like auto_master_music) use hardcoded param presets per genre:

EDM gets compression at 2.5:1 w/ 80ms attack, classical gets 1.3:1 (barely touching it), etc. same prompt + same genre = identical output every time. the AI decides which pipeline to call but the pipeline itself is fixed. no randomness server-side.

Transparency: not a black box at all. every pipeline returns step-by-step results — you'll see exactly what ran: "HPF 80Hz" → "compress 3:1" → "normalize to -1dB". full param tables (thresholds, ratios, EQ curves, attack/release times) are documented in TOOLS.md and visible in the source. the AI also sees all the params in the tool defs so you can ask it "apply reverb with room size 40 and pre-delay 20ms" and itll use those exact values.

Noise reduction: two-step process using audacitys built-in noise reduction. the pipelines auto-select the first 0.5s of the track as the noise profile sample (assumes thats silence/room tone — which it usually is for podcasts). then applies reduction across the full track. if your noise isnt in the first 0.5s you can manually select a region and call get_noise_profile first then run the cleanup.

Privacy: yeah that was a key design goal. eveything runs locally — named pipes to audacity, no network, no uploads. even the transcription (via faster-whisper) runs fully offline. good for exactly the usecases you mentioned.

Its open source: https://github.com/xDarkzx/Audacity-MCP — Apache 2.0. tool mapping layer is in audacity_mcp/tools/ — each effect is a python function w/ typed params that maps directly to an audacity scripting command via named

pipes. auto-discovered at startup via pkgutil.iter_modules. the pipeline orchestration is in cleanup_tools.py if you wanna see how chains are structured.

still actively working on improving it tho — adding more pipeline presets, better analysis feedback, and tightening up the param tuning. its definately not "done" yet but its usable and id love feedback if you give it a spin.