Full-duplex conversational barge-in arbitrator classifying user interruptions, backchannels, and acoustic echo with context rollback.
- ✓Actively maintained (<30d)
- ✓Clear description
- ✓Topics declared
- ✓Documented (README)
- !Licence file present but not machine-readable
claude mcp add genpark-conversational-barge-in-interruption-arbitrator-skill -- uvx genpark-conversational-barge-in-interruption-arbitrator-skill{
"mcpServers": {
"genpark-conversational-barge-in-interruption-arbitrator-skill": {
"command": "uvx",
"args": ["genpark-conversational-barge-in-interruption-arbitrator-skill"]
}
}
}MCP Servers overview
# genpark-conversational-barge-in-interruption-arbitrator-skill
<div align="center">
[](https://www.python.org/)
[](LICENSE)
[](https://genpark.ai/mcp)
[](https://genpark.ai)
[-brightgreen.svg?style=for-the-badge)](requirements.txt)
<p align="center">
<b>Production-Grade Real-Time Voice Agent & Conversational Audio Skill</b> • <b>100% Standard Library Python</b> • <b>Native Model Context Protocol (MCP)</b>
</p>
[🌐 GenPark MCP Hub Showcase](https://genpark.ai/mcp) • [📦 Official Website](https://genpark.ai) • [📖 Documentation](#quickstart)
</div>
---
## 📌 Overview & Capability
**genpark-conversational-barge-in-interruption-arbitrator-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**: Full-duplex conversational barge-in arbitrator classifying user interruptions, backchannels, and acoustic echo with context rollback.
### ⚡ 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
```mermaid
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
```bash
python example_usage.py
```
### 2. Programmatic Integration
```python
from client import ConversationalBargeInArbitrator
client = ConversationalBargeInArbitrator()
result = client.run_benchmark_barge_in_arbitration()
print(result)
```
---
## 🔌 Model Context Protocol (MCP) Setup
Connect this skill to **Claude Desktop**, **Cursor**, or any MCP-compliant client:
### `claude_desktop_config.json`
```json
{
"mcpServers": {
"genpark-conversational-barge-in-interruption-arbitrator-skill": {
"command": "python",
"args": ["/path/to/genpark-conversational-barge-in-interruption-arbitrator-skill/mcp_server.py"]
}
}
}
```
---
## 📊 Technical Specifications
| Parameter | Type | Required | Description |
|---|---|:---:|---|
| `query_payload` | `string` / `dict` | Yes | Primary audio frame, transcript, or telemetry event payload |
| `output_format` | `json` / `dict` | Yes | Standardized 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](https://genpark.ai/mcp).
#### Q3: How do I test this MCP server locally?
Run `python mcp_server.py --test` to verify MCP protocol discovery and tool schema negotiation.
---
<div align="center">
<sub>Maintained with ❤️ by <b><a href="https://genpark.ai">GenPark AI Engineering</a></b> • Powering Next-Gen Real-Time Conversational Agents 🌍</sub>
</div>
What people ask about genpark-conversational-barge-in-interruption-arbitrator-skill
What is alphaparkinc/genpark-conversational-barge-in-interruption-arbitrator-skill?
+
alphaparkinc/genpark-conversational-barge-in-interruption-arbitrator-skill is mcp servers for the Claude AI ecosystem. Full-duplex conversational barge-in arbitrator classifying user interruptions, backchannels, and acoustic echo with context rollback. It has 7 GitHub stars and its last recorded update is dated 2026-09-27.
How do I install genpark-conversational-barge-in-interruption-arbitrator-skill?
+
You can install genpark-conversational-barge-in-interruption-arbitrator-skill by cloning the repository (https://github.com/alphaparkinc/genpark-conversational-barge-in-interruption-arbitrator-skill) or following the README instructions on GitHub. ClaudeWave also provides quick install blocks on this page.
Is alphaparkinc/genpark-conversational-barge-in-interruption-arbitrator-skill safe to use?
+
Our security agent has analyzed alphaparkinc/genpark-conversational-barge-in-interruption-arbitrator-skill and assigned a Trust Score of 80/100 (tier: Trusted). See the full breakdown of passed checks and flags on this page.
Who maintains alphaparkinc/genpark-conversational-barge-in-interruption-arbitrator-skill?
+
alphaparkinc/genpark-conversational-barge-in-interruption-arbitrator-skill is maintained by alphaparkinc. The last recorded GitHub activity is dated 2026-09-27, with 0 open issues.
Are there alternatives to genpark-conversational-barge-in-interruption-arbitrator-skill?
+
Yes. On ClaudeWave you can browse similar mcp servers at /categories/mcp, sorted by popularity or recent activity.
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