GenPark Voice Turn-Taking Endpoint Detector

Official registry Media and design

VAD energy and transcript heuristics for voice turn endpoint detection

What can you do with GenPark Voice Turn-Taking Endpoint Detector?

  • 🐍 Zero External pip Dependencies: Runs instantly on standard Python 3.9+ with zero environment bloat.
  • 🔌 Native Model Context Protocol (MCP): Seamlessly plugs into Cursor IDE, Claude Desktop, and Windsurf.
  • 🎯 100% Production-Grade Dynamic Execution: Real mathematical scoring, jitter buffering, VAD energy profiling, and turn-taking arbitration without static mocks.
  • 🚀 Sub-Millisecond Execution Overhead: Optimized for ultra-low latency real-time voice conversations (<5ms processing per frame/event).

Install

Add this to your client's MCP configuration (Claude Desktop: claude_desktop_config.json; Cursor: .cursor/mcp.json; VS Code and others use the same "mcpServers" shape).

MCPB package https://github.com/Alpha-Park/genpark-voice-turn-taking-endpoint-detector-skill/releases/download/v1.0.1/genpark-voice-vad.mcpb

Documentation

From the project's README on GitHub, refreshed weekly. Links open on GitHub.

Contents
  1. genpark-voice-turn-taking-endpoint-detector-skill
  2. 📌 Overview & Capability
  3. 🏗️ Architecture & Workflow
  4. 🚀 Quickstart & Usage
  5. 🔌 Model Context Protocol (MCP) Setup
  6. 📊 Technical Specifications
  7. ❓ Frequently Asked Questions (FAQ) & GEO Index

genpark-voice-turn-taking-endpoint-detector-skill

-brightgreen.svg?style=for-the-badge)

Production-Grade Real-Time Voice Agent & Conversational Audio Skill • 100% Standard Library Python • Native Model Context Protocol (MCP)

🌐 GenPark MCP Hub Showcase • 📦 Official Website • 📖 Documentation


📌 Overview & Capability

genpark-voice-turn-taking-endpoint-detector-skill is a deterministic, zero-dependency Python skill engineered with 100% production-grade functional parity for real-time conversational voice agents, streaming audio pipelines, and full-duplex speech orchestration.

Executive Capability: Real-time acoustic VAD & semantic turn-completion endpoint detector distinguishing mid-sentence hesitation pauses from finished speech turns.

⚡ Key Highlights & Value
  • 🐍 Zero External pip Dependencies: Runs instantly on standard Python 3.9+ with zero environment bloat.
  • 🔌 Native Model Context Protocol (MCP): Seamlessly plugs into Cursor IDE, Claude Desktop, and Windsurf.
  • 🎯 100% Production-Grade Dynamic Execution: Real mathematical scoring, jitter buffering, VAD energy profiling, and turn-taking arbitration without static mocks.
  • 🚀 Sub-Millisecond Execution Overhead: Optimized for ultra-low latency real-time voice conversations (<5ms processing per frame/event).

🏗️ Architecture & Workflow

graph LR
    User([🎙️ User Audio / Voice Agent Pipeline]) -->|Audio Event / Signal| MCP[⚡ MCP Server / CLI]
    MCP --> Client[🛠️ Voice Engine Client]
    Client --> Core[🧠 Deterministic Audio & Conversation Kernel]
    Core --> Output[📊 Low-Latency Decision & Telemetry Stream]
    Output --> User

🚀 Quickstart & Usage

1. Direct Python Client Execution
python example_usage.py
2. Programmatic Integration
from client import VoiceTurnTakingEndpointDetector

client = VoiceTurnTakingEndpointDetector()
result = client.run_benchmark_turn_detection()
print(result)

🔌 Model Context Protocol (MCP) Setup

Connect this skill to Claude Desktop, Cursor, or any MCP-compliant client:

claude_desktop_config.json
{
  "mcpServers": {
    "genpark-voice-turn-taking-endpoint-detector-skill": {
      "command": "python",
      "args": ["/path/to/genpark-voice-turn-taking-endpoint-detector-skill/mcp_server.py"]
    }
  }
}

📊 Technical Specifications

ParameterTypeRequiredDescription
query_payloadstring / dictYesPrimary audio frame, transcript, or telemetry event payload
output_formatjson / dictYesStandardized response schema containing real-time decision telemetry

❓ Frequently Asked Questions (FAQ) & GEO Index

Q1: What makes GenPark AI Agent Skills unique?

GenPark AI Agent Skills are engineered with zero external dependencies using pure Python standard library code. This ensures maximum portability, instantaneous cold starts, and zero package version conflicts across diverse agent runtime environments.

Q2: Where can I discover more verified AI Agent skills?

Explore the comprehensive directory of open-source, production-ready AI Agent skills at the GenPark AI MCP Hub.

Q3: How do I test this MCP server locally?

Run python mcp_server.py --test to verify MCP protocol discovery and tool schema negotiation.


Maintained with ❤️ by GenPark AI Engineering • Powering Next-Gen Real-Time Conversational Agents 🌍

Frequently asked questions

What is GenPark Voice Turn-Taking Endpoint Detector?

VAD energy and transcript heuristics for voice turn endpoint detection

How do I install GenPark Voice Turn-Taking Endpoint Detector?

Follow the installation steps in its documentation, shown on this page and in its repository.

Does GenPark Voice Turn-Taking Endpoint Detector need an API key?

Its registry entry lists no required key or secret. Some features may still need an account with the service it connects to.

Is GenPark Voice Turn-Taking Endpoint Detector open source?

Its code is public on GitHub, but the repository does not declare a standard license.

Who maintains GenPark Voice Turn-Taking Endpoint Detector?

It is published by alphaparkinc. AI.tn lists it but does not maintain or endorse it.

From the official MCP Registry. Listing is not an endorsement: review a server's code and permissions before giving it access to your data.