F
licenseNot graded
qualityC
maintenanceEnables agents to analyze speech prosody and vocal sentiment, including speech rate, pitch variance, and cognitive fatigue, to dynamically calibrate response pacing.
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SpeechPulse
by sophieMiao
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- FlicenseNot gradedqualityBmaintenanceEnables MCP-compliant agents to analyze speech prosody and vocal sentiment from audio-derived input, measuring speech rate, pitch variance, and user cognitive fatigue. Exposes these deterministic results over JSON-RPC so clients can dynamically calibrate their response pacing.7-
- FlicenseNot gradedqualityBmaintenanceEnables decoding of acoustic signals such as fundamental frequency, speaking rate, jitter, and pause ratio together with semantic sentiment to infer high-dimensional emotional states and emit real-time expressive TTS prosody directives. It runs as a zero-dependency JSON-RPC 2.0 MCP server over stdio, exposing these capabilities as callable tools.7-
- FlicenseNot gradedqualityNot gradedmaintenanceExposes an MCP tool that fuses acoustic prosody measurements (F0, speaking rate, jitter, pause ratio) with semantic sentiment to infer high-dimensional emotional states from speech. Returns tone, speaking-rate multiplier, and pitch-shift directives so agents can drive real-time expressive TTS modulation through JSON-RPC over stdio.7-
- AlicenseAqualityCmaintenanceProvides local audio analysis tools for LLMs, enabling transcription, conversation dynamics, prosody analysis, and visual inspection without API keys.8MIT
TDQS
A3.8/5.0
Scored across 5 tools
Disambiguation3/5
Tools have distinct focuses (emotion, urgency, sarcasm, health) but full_analysis overlaps by combining all three analyses, creating potential confusion for an agent choosing between individual and combined tools.
Naming Consistency3/5
Most tools follow a verb_noun pattern (analyze_audio, assess_urgency, detect_sarcasm) but full_analysis and health_check deviate, mixing noun phrases and lacking consistent verb usage.
Tool Count4/5
With 5 tools, the server covers core audio analysis tasks (emotion, urgency, sarcasm) plus a combined analysis and health check, which is well-scoped and reasonable for the domain.
Completeness3/5
The set covers emotion, urgency, and sarcasm detection, but lacks a dedicated transcription tool (ASR is optional via parameter) and other potential features like speaker identification, leaving moderate gaps.