The full upstream README, mirrored here for reference. Install config, tool schemas, adoption signals, and an original overview live on the Genpark Voice Vad listing page.
Energy and transcript heuristics for voice turn endpoint detection.
This is a heuristic endpoint detector over precomputed dB energies and a transcript. It does not decode audio, transcribe speech, or run a trained VAD model. Confidence values are heuristic scores, not calibrated probabilities.
Python 3.9 or newer. The library and stdio MCP server have no runtime dependencies.
PyPI publication is pending account setup. The intended PyPI project is genpark-voice-vad;
do not assume pip install genpark-voice-vad is available until the project is published.
After installing the wheel, configure your MCP client with the installed command:
If the command is not on PATH, use its absolute path or python -m genpark_voice_vad
with the same interpreter where you installed the wheel.
The GitHub release also contains a .mcpb bundle for clients supporting desktop extensions.
That bundle requires a Python 3.9+ interpreter on PATH; it bundles the server source.
Available tools: analyze_turn_status, calibrate_acoustic_thresholds, predict_semantic_closure, run_benchmark_turn_detection.
tools/list returns required arguments and JSON schemas.
Each MCP process holds its own state. Benchmark tools use isolated instances.
python mcp_server.py --test runs the deterministic example; it is not a protocol conformance test.
The MCP client check exercises initialize, tools/list, tools/call and ping over stdio.
GitHub source and release artifacts are the primary distribution until PyPI is configured. Registry submissions are tracked separately; a manifest is not proof of registry acceptance. See PUBLISHING.md for the repeatable PyPI workflow.
MIT license. Maintained by GenPark.