Supertonic3

Local, on-device TTS for Claude & Cursor, powered by Supertonic 3. No API key. No cloud. An internal tool open-sourced by Halozen — we build AI compliance intelligence for construction.

Not affiliated with Supertone Inc.

Expose speak, list_voices, and list_expressions to Claude Desktop, Cursor, or any MCP client over STDIO.

Quick start (TTHW < 3 min)

git clone https://github.com/nextic-tech/supertonic3-mcp && cd supertonic3-mcp
python3 -m venv .venv && source .venv/bin/activate
pip install -e ".[dev]"

# Optional: pre-download model for offline use (~400MB)
supertonic3-mcp preload

# Run MCP server (STDIO)
supertonic3-mcp

Cursor MCP config

Add to .cursor/mcp.json (or Cursor Settings → MCP):

{
  "mcpServers": {
    "supertonic3": {
      "command": "/absolute/path/to/supertonic-tts/.venv/bin/supertonic3-mcp",
      "args": []
    }
  }
}

First server start downloads the Supertonic model into ~/.cache/supertonic3/ unless you ran preload first.

Tools

speak parameters

• text — 1–5000 characters; expression tags allowed
• voice_id — optional (M1, F1, …)
• language — ISO 639-1 (en, ko, ja, …). For non-English text, always set language=. Defaults to en.
• speed — 0.7 to 2.0 (SDK range)
• play — if true, plays audio on this machine via afplay (macOS) or aplay (Linux). Unsupported on Windows.

WAV files are written to /tmp/supertonic_*.wav (macOS/Linux). Windows is not supported for synthesis output paths in v1.0.

Example return:

Audio saved to /tmp/supertonic_abc123.wav (1.4s, voice: M1, lang: en)

Performance (this repo)

Measured on Apple M3, supertonic 1.3.1 — see benchmark/results.md.

FSL = time from synthesize() through WAV written (no streaming, no play=True).

Re-run: python benchmark/run.py

Offline use

supertonic3-mcp preload

Downloads ONNX weights atomically to ~/.cache/supertonic3/ and prints SHA256 checksums. After preload, synthesis works without network access.

Development

pip install -e ".[dev]"
pytest

Tests mock the Supertonic SDK (no network in CI).

Coming in v1.1

• listen() — Whisper speech-to-text (pip install supertonic3-mcp[stt])
• SSE transport + Docker image for remote agents
• PyPI publish workflow

License

MIT (this package). Supertonic SDK is MIT; model weights use OpenRAIL-M.

Disclaimer

AI-generated speech is not a substitute for certified safety, legal, or medical guidance. For demonstration purposes only.