genpark-multimodal-voice-prosody-sentiment-analyzer-skill
OfficialClick on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@genpark-multimodal-voice-prosody-sentiment-analyzer-skillAnalyze prosody and vocal fatigue in this voice recording."
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
genpark-multimodal-voice-prosody-sentiment-analyzer-skill
🌐 GenPark MCP Hub • 📦 GenPark Official • 📖 Documentation
📌 Overview & Capability
genpark-multimodal-voice-prosody-sentiment-analyzer-skill is a deterministic, high-performance, zero-dependency Python tool and native Model Context Protocol (MCP) server engineered for next-generation personal agents, multi-agent frameworks, and autonomous developer workflows.
Executive Capability: Multi-modal speech prosody and vocal sentiment analyzer detecting speech rate, pitch variance, and user cognitive fatigue to dynamically calibrate agent response pacing.
⚡ Key Highlights
🐍 Zero External
pipDependencies: Implemented entirely with pure Python standard library for instant zero-overhead execution.🔌 Native Model Context Protocol (MCP): Plugs directly into any MCP-compliant client via JSON-RPC 2.0 stdio.
⚡ Sub-Millisecond Execution: Slashes token burn and latency by resolving routine agent tasks deterministically without frontier LLM round-trips.
🛡️ Production-Hardened: Comprehensive error handling, boundary validation, and telemetry.
Related MCP server: SpeechPulse
🏗️ Architecture
graph LR
Agent([🤖 Autonomous Agent / IDE]) -->|MCP Protocol / JSON-RPC| Server[⚡ genpark-multimodal-voice-prosody-sentiment-analyzer-skill Server]
Server --> Core[🧠 Deterministic Processing Core]
Core --> Out[📊 Actionable Result & Telemetry]
Out --> Agent🚀 Quickstart & Usage
1. Direct Python Client Execution
python example_usage.py2. Programmatic Integration
from client import MultimodalVoiceProsodyAnalyzer
client = MultimodalVoiceProsodyAnalyzer()
result = client.run_voice_prosody_benchmark()
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-multimodal-voice-prosody-sentiment-analyzer-skill": {
"command": "python",
"args": ["/path/to/genpark-multimodal-voice-prosody-sentiment-analyzer-skill/mcp_server.py"]
}
}
}Direct MCP Testing
python mcp_server.py --test📊 Technical Specifications
Parameter | Type | Required | Description |
|
| Yes | Primary context, text, or task input |
|
| No | Execution flags, thresholds, or sensitivity bounds |
This server cannot be deployed
Maintenance
Related MCP Connectors
Hosted speech-to-text + speech emotion/tone analysis for agents. No install; trial keys built in.
AI call analysis and voice agents for sales teams. Signup, usage, agents and call data over MCP.
Remote MCP server that returns sentiment analysis results from SentinelScan API.
Fuses biometric signals into a stress score (0-100) for AI adaptation. MCP + A2A native.
Related MCP Servers
- AlicenseAqualityAmaintenanceOfficial MCP server for the Vocametrix voice analysis API. Gives AI assistants direct access to clinical voice metrics (AVQI, DSI, jitter/shimmer, CPP), pronunciation assessment, speech transcription, prosody similarity, and AI-powered therapy planning. More than 40 endpoints for SLPs, voice researchers, and healthtech developers.39365 npmMIT
- AlicenseAqualityDmaintenanceAnalyzes speech audio to detect emotions, urgency, and sarcasm using prosodic features.52MIT
- AlicenseNot gradedqualityBmaintenanceEnables voice-first interactions with AI agents and MCP tools, supporting speech input/output, STT/TTS, and a provider-independent agent core.1MIT
- FlicenseNot gradedqualityBmaintenanceEnables acoustic vocal emotion, prosodic valence, and customer frustration analysis on audio queries via the Model Context Protocol, letting MCP-compliant clients obtain structured emotional telemetry and deterministic results.7-