nefesh-mcp-server

Returns:
- state: calm | relaxed | focused | stressed | acute_stress
- stress_score: 0-100 (lower = calmer)
- confidence: 0.0-1.0 (based on signal quality and device type)
- suggested_action: maintain_engagement | simplify_and_focus | de-escalate_and_shorten | pause_and_ground
- action_reason: human-readable explanation of why this action was suggested
- adaptation_effectiveness (on 2nd+ call): shows whether your previous suggested_action actually reduced stress — contains previous_action, stress_delta, and effective boolean. Use this to self-improve.

Use suggested_action to adapt your response: calm/relaxed = full complexity, focused = shorter and structured, stressed = max 2 sentences, acute_stress = one grounding sentence only.

Requires a prior ingest call to have data. Not a medical device.

Required: session_id + timestamp (ISO 8601) + at least one signal.
Send whatever you have — the API fuses all signals into one state.

Common signals (highest impact):
- heart_rate (bpm, 30-220) + rmssd (ms) — cardiovascular
- tone: calm | tense | anxious | hostile — vocal
- sentiment: -1.0 to 1.0 — textual
- expression: relaxed | neutral | tense — visual

For trigger memory (cross-session psychological tracking):
- Include subject_id (consistent per user, hashed)
- Include user_message + ai_response to detect stress topics

Returns same fields as get_human_state plus signals_received list and topics_detected.

source_device is optional but improves confidence scoring. Not a medical device.

Returns which conversation topics consistently cause stress (active triggers) and which have been resolved over time.

- active triggers: topics where stress was elevated across multiple sessions. Tread carefully.
- resolved triggers: topics where stress has decreased. Safe to explore deeper.

Each trigger includes observation_count, avg_score, peak_score, and last_seen.

Requires prior ingest calls with the same subject_id. Not a medical device.

Returns timestamped datapoints with stress_score, state, and heart_rate for each observation.
Includes an overall trend: rising | falling | stable.

Use minutes parameter to control the lookback window (default: 5, max: 60).
Useful for detecting stress patterns during a conversation. Not a medical device.