How do I install GenPark Realtime Voice Agent Latency Telemetry?

Copy the stdio config for Cursor, Claude Desktop, Claude Code, or VS Code on this page. It uses the publisher's install, not a PlugMCP proxy.

Does GenPark Realtime Voice Agent Latency Telemetry need an API key?

No required environment variable is listed on this record.

What transport does GenPark Realtime Voice Agent Latency Telemetry use?

GenPark Realtime Voice Agent Latency Telemetry runs locally over stdio.

When was GenPark Realtime Voice Agent Latency Telemetry last checked?

Last checked 2026-11-09. Voice pipeline timestamp telemetry profiler and percentile latency calculator

GenPark Realtime Voice Agent Latency Telemet MCP server

Power your agent

Add this server

The publisher's own command. Not a PlugMCP endpoint.

Add to Cursor Add to VS Code Run on PlugMCP

Host a copy with our keys and logs.

Local command

mcpb https://github.com/Alpha-Park/genpark-realtime-voice-agent-latency-telemetry-skill/releases/download/v1.0.1/genpark-voice-latency.mcpb

Claude Code has no install link for a local command. Copy the command below and run it in a terminal.

shClaude Code

1claude mcp add io.github.alphaparkinc-genpark-realtime-voice-agent-latency-telemetry-skill -- mcpb https://github.com/Alpha-Park/genpark-realtime-voice-agent-latency-telemetry-skill/releases/download/v1.0.1/genpark-voice-latency.mcpb

Run in a terminal.

jsonClaude Desktop

1{2  "mcpServers": {3    "io.github.alphaparkinc-genpark-realtime-voice-agent-latency-telemetry-skill": {4      "command": "mcpb",5      "args": [6        "https://github.com/Alpha-Park/genpark-realtime-voice-agent-latency-telemetry-skill/releases/download/v1.0.1/genpark-voice-latency.mcpb"7      ]8    }9  }10}

claude_desktop_config.json

Local · mcpbPublisher installStep-by-step: add this in Claude

Remote URL or a command on your machine? How the two installs differ

Run on PlugMCP

Host a copy with our keys and logs.

A new server you create. It is not this listing's official endpoint. Use the publisher install when you want their URL and their credentials.

Launch

Server facts

Local

Transport: stdio
Version: 1.0.1
Last checked

Tools

No tool list yet. Remote servers get one after the first health check.

FAQ

Questions

genpark-realtime-voice-agent-latency-telemetry-skill

-brightgreen.svg?style=for-the-badge) 🌐 GenPark MCP Hub Showcase • 📦 Official Website • 📖 Documentation

📌 Overview & Capability

genpark-realtime-voice-agent-latency-telemetry-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: End-to-end conversational voice agent latency telemetry profiler tracking VAD, STT, LLM-TTFT, TTS-TTFB, and playout bottlenecks.

⚡ 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 RealtimeVoiceLatencyTelemetry

client = RealtimeVoiceLatencyTelemetry()
result = client.run_benchmark_telemetry_profiling()
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-realtime-voice-agent-latency-telemetry-skill": {
      "command": "python",
      "args": ["/path/to/genpark-realtime-voice-agent-latency-telemetry-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.

Q3: How do I test this MCP server locally?

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