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Nefesh — Real-Time Human State Awareness for AI

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by nefesh-ai · Python

Fuses biometric signals into a stress score (0-100) for AI adaptation. MCP + A2A native.

ai.nefesh/human-state — MCP Server

ai.nefesh/human-state is a Model Context Protocol (MCP) and Agent-to-Agent (A2A) server that fuses biometric signals into a unified human stress score. It aggregates inputs such as heart rate, voice, facial expression, and text sentiment, returning a machine-readable state with an action your agent can follow.

🛠️ Key Features

  • Model Context Protocol (MCP) server
  • Agent-to-Agent (A2A) support
  • Produces a stress score on a 0–100 scale
  • Accepts biometric and expression signals (heart rate, voice, facial expression, text sentiment)
  • Closed-loop feedback: 2nd+ call includes adaptation_effectiveness

🚀 Use Cases

  • Real-time AI adaptation based on a user’s physiological stress state
  • Agent workflows that adjust behavior after evaluating whether a prior approach worked

⚡ Developer Benefits

  • Avoids “prompt engineering” for adaptation
  • Returns a unified, machine-readable state and action
  • Provides adaptation_effectiveness for iterative improvement