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Nefesh — Real-Time Human State Awareness for AI

nefesh-ai/nefesh-mcp-server
6 toolsauthHTTPregistry active
Summary

Exposes six MCP tools for reading and tracking human physiological state in real time. Send biometric data (heart rate, HRV, voice tone, facial expression, sentiment) via `ingest` and get back a 0-100 stress score plus a `suggested_action` like "de-escalate" or "simplify". The standout feature is `adaptation_effectiveness`, which tells your agent whether its previous response actually lowered stress, creating a closed-loop feedback system. Also available as an A2A agent at `https://mcp.nefesh.ai/a2a` for agent-to-agent collaboration. Free tier includes 1,000 calls per month with no credit card. Reach for this when you want your AI to adjust tone, pacing, or complexity based on measurable human state instead of guessing from chat history.

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Tools

Public tool metadata for what this MCP can expose to an agent.

6 tools
get_human_stateGet current unified human state for a session. Call this before generating important responses. 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) - suggest...1 params

Get current unified human state for a session. Call this before generating important responses. 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) - suggest...

Parameters* required
session_idstring
ingestSend biometric signals from any sensor, get unified state back. 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) — card...35 params

Send biometric signals from any sensor, get unified state back. 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) — card...

Parameters* required
edavalue
gazevalue
sdnnvalue
spo2value
tonevalue
pnn50value
rmssdvalue
posturevalue
urgencyvalue
mean_ibivalue
ibi_countvalue
sentimentvalue
timestampstring
confidencevalue
engagementvalue
expressionvalue
heart_ratevalue
session_idstring
subject_idvalue
sleep_stagevalue
speech_ratevalue
stress_scorevalue
glucose_mg_dlvalue
glucose_trendvalue
source_devicevalue
activity_levelvalue
cognitive_loadvalue
eeg_beta_powervalue
glucose_mmol_lvalue
eeg_alpha_powervalue
eeg_theta_powervalue
respiratory_ratevalue
skin_temperaturevalue
pitch_variabilityvalue
steps_last_minutevalue
get_trigger_memoryRetrieve psychological trigger profile for a subject. 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...1 params

Retrieve psychological trigger profile for a subject. 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...

Parameters* required
subject_idstring
get_session_historyGet state history for a session over time. 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...2 params

Get state history for a session over time. 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...

Parameters* required
minutesinteger
default: 5
session_idstring
request_api_keyRequest a free Nefesh API key. No existing API key needed for this call. Flow: call this → developer clicks email link → poll check_api_key_status with the returned request_id every 10 seconds until status is 'ready'. Free tier: 1,000 calls/month, all signal types, 10 req/min....1 params

Request a free Nefesh API key. No existing API key needed for this call. Flow: call this → developer clicks email link → poll check_api_key_status with the returned request_id every 10 seconds until status is 'ready'. Free tier: 1,000 calls/month, all signal types, 10 req/min....

Parameters* required
emailstring
check_api_key_statusPoll for API key activation after calling request_api_key. No existing API key needed. Returns status: 'pending' (keep polling) or 'ready' (includes api_key — store it immediately, returned once only). Poll every 10 seconds. Expires after 15 minutes.1 params

Poll for API key activation after calling request_api_key. No existing API key needed. Returns status: 'pending' (keep polling) or 'ready' (includes api_key — store it immediately, returned once only). Poll every 10 seconds. Expires after 15 minutes.

Parameters* required
request_idstring

Nefesh MCP + A2A Server

A Model Context Protocol and Agent-to-Agent (A2A) server that gives AI agents real-time awareness of human physiological state.

What it does

Send sensor data (heart rate, voice, facial expression, text sentiment), get back a unified state with a machine-readable action your agent can follow directly. Zero prompt engineering required.

On the 2nd+ call, the response includes adaptation_effectiveness — telling your agent whether its previous approach actually worked. A closed-loop feedback system for self-improving agents.

Adaptation Effectiveness (Closed-Loop)

Most APIs give you a state. Nefesh tells you whether your reaction to that state actually worked.

On the 2nd+ call within a session, every response includes:

{
  "state": "focused",
  "stress_score": 45,
  "suggested_action": "simplify_and_focus",
  "adaptation_effectiveness": {
    "previous_action": "de-escalate_and_shorten",
    "previous_score": 68,
    "current_score": 45,
    "stress_delta": -23,
    "effective": true
  }
}

Your agent can read effective: true and know its previous de-escalation worked. If effective: false, the agent adjusts its strategy. No other human-state system provides this feedback loop.

Setup

Option A: Connect first, get a key through your agent (fastest)

Add the config without an API key — your agent will get one automatically.

{
  "mcpServers": {
    "nefesh": {
      "url": "https://mcp.nefesh.ai/mcp"
    }
  }
}

Then ask your agent:

"Get me a free Nefesh API key using my email address"

The agent calls request_api_key → you click one email link → the agent picks up the key. No signup form, no manual copy-paste. After that, add the key to your config for future sessions:

{
  "mcpServers": {
    "nefesh": {
      "url": "https://mcp.nefesh.ai/mcp",
      "headers": {
        "X-Nefesh-Key": "nfsh_free_..."
      }
    }
  }
}

Option B: Get a key first, then connect

Sign up at nefesh.ai/signup (1,000 calls/month, no credit card), then add the config with your key:

{
  "mcpServers": {
    "nefesh": {
      "url": "https://mcp.nefesh.ai/mcp",
      "headers": {
        "X-Nefesh-Key": "YOUR_API_KEY"
      }
    }
  }
}

Agent-specific config files

AgentConfig file
Cursor~/.cursor/mcp.json
Windsurf~/.codeium/windsurf/mcp_config.json
Claude Desktop~/Library/Application Support/Claude/claude_desktop_config.json
Claude Code.mcp.json (project root)
VS Code (Copilot).vscode/mcp.json or ~/Library/Application Support/Code/User/mcp.json
Clinecline_mcp_settings.json (via UI: "Configure MCP Servers")
Continue.dev.continue/config.yaml
Roo Code.roo/mcp.json
Kiro (Amazon)~/.kiro/mcp.json
OpenClaw~/.config/openclaw/mcp.json
JetBrains IDEsSettings > Tools > MCP Server
Zed~/.config/zed/settings.json (uses context_servers)
OpenAI Codex CLI~/.codex/config.toml
Goose CLI~/.config/goose/config.yaml
ChatGPT DesktopSettings > Apps > Add MCP Server (UI)
Gemini CLISettings (UI)
AugmentSettings Panel (UI)
ReplitIntegrations Page (web UI)
LibreChatlibrechat.yaml (self-hosted)
VS Code (Copilot) — uses servers instead of mcpServers
{
  "servers": {
    "nefesh": {
      "type": "http",
      "url": "https://mcp.nefesh.ai/mcp",
      "headers": {
        "X-Nefesh-Key": "<YOUR_API_KEY>"
      }
    }
  }
}
Zed — uses context_servers in settings.json
{
  "context_servers": {
    "nefesh": {
      "settings": {
        "url": "https://mcp.nefesh.ai/mcp",
        "headers": {
          "X-Nefesh-Key": "<YOUR_API_KEY>"
        }
      }
    }
  }
}
OpenAI Codex CLI — uses TOML in ~/.codex/config.toml
[mcp_servers.nefesh]
url = "https://mcp.nefesh.ai/mcp"
Continue.dev — uses YAML in .continue/config.yaml
mcpServers:
  - name: nefesh
    type: streamable-http
    url: https://mcp.nefesh.ai/mcp

All agents connect via Streamable HTTP — no local installation required.

A2A Integration (Agent-to-Agent Protocol v1.0)

Nefesh is also available as an A2A-compatible agent. While MCP handles tool-calling (your agent calls Nefesh), A2A enables agent-collaboration — other AI agents can communicate with Nefesh as a peer.

Agent Card: /.well-known/agent-card.json

A2A Endpoint: POST https://mcp.nefesh.ai/a2a (JSON-RPC 2.0)

A2A SkillDescription
get-human-stateStress state (0-100), suggested_action, adaptation_effectiveness
ingest-signalsSend biometric signals, receive unified state
get-trigger-memoryPsychological trigger profile (active vs resolved)
get-session-historyTimestamped history with trend

Same authentication as MCP — X-Nefesh-Key header or Authorization: Bearer token. Free tier works on both protocols.

Source: nefesh-ai/nefesh-a2a · Docs: nefesh.ai/docs/a2a

MCP Tools

ToolAuthDescription
request_api_keyNoRequest a free API key. You MUST ask the user for their real email first. Do not invent or guess emails. The user receives a verification link they must click. Poll with check_api_key_status until ready.
check_api_key_statusNoPoll for API key activation using the same email the user provided. Returns pending or ready with API key.
get_human_stateYesGet stress state (0-100), suggested_action (maintain/simplify/de-escalate/pause), and adaptation_effectiveness — a closed-loop showing whether your previous action reduced stress.
ingestYesSend biometric signals (heart rate, HRV, voice tone, expression, sentiment, 30+ fields) and get unified state back. Include subject_id for trigger memory.
get_trigger_memoryYesGet psychological trigger profile — which topics cause stress (active) and which have been resolved over time.
get_session_historyYesGet timestamped state history with trend (rising/falling/stable).

How self-provisioning works

Your AI agent can get a free API key autonomously. You only click one email link.

  1. Agent asks you: "What is your email address?"
  2. Agent calls request_api_key(your_real_email). No API key needed for this call.
  3. You receive a verification email and click the link
  4. Agent polls check_api_key_status(your_real_email) every 10 seconds
  5. Once verified, the agent receives the API key and can use all other tools

Important: The agent must use your real, accessible email address. Disposable emails are blocked. The verification link must be clicked by you to activate the key.

Free tier: 1,000 calls/month, all signal types, 10 req/min. No credit card.

Quick test

After adding the config, ask your AI agent:

"What tools do you have from Nefesh?"

It should list the 6 tools above.

Pricing

PlanPriceAPI Calls
Free$01,000/month, no credit card
Solo$25/month50,000/month
EnterpriseCustomCustom SLA

CLI Alternative

Prefer the terminal over MCP? Use the Nefesh CLI (10-32x lower token cost than MCP for AI agents):

npm install -g @nefesh/cli
nefesh ingest --session test --heart-rate 72 --tone calm
nefesh state test --json

GitHub: nefesh-ai/nefesh-cli

Gateway Alternative

Want the AI to adapt automatically? Use the Nefesh Cognitive Compute Router. Change your LLM base URL to gateway.nefesh.ai and the gateway adjusts system prompt and temperature based on biometric state. Three modes: OpenAI-compatible (/v1/chat/completions), Anthropic passthrough (/v1/messages), and Unified Anthropic for any backend. Zero code changes.

GitHub: nefesh-ai/nefesh-gateway

Human State Protocol (HSP)

Nefesh implements and maintains the Human State Protocol, an open specification for exchanging human physiological state between AI systems. HSP defines a standard JSON format for stress scores, behavioral recommendations, and adaptation feedback so any agent can produce or consume human state data interoperably. Apache 2.0.

GitHub: nefesh-ai/human-state-protocol · Docs: nefesh.ai/docs/hsp

Documentation

  • Full API Reference
  • Quick Start
  • State Mapping
  • MCP Server · Source
  • A2A Server · Source
  • Cognitive Compute Router (Gateway) · Source
  • CLI · Source
  • Human State Protocol (HSP) · Source
  • A2A Agent Card
  • A2A Protocol Spec

Privacy

  • No video or audio uploads — edge processing runs client-side
  • No PII stored
  • GDPR/BIPA compliant — cascading deletion via delete_subject
  • Not a medical device — for contextual AI adaptation only

License

MIT — see LICENSE.

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UpdatedApr 3, 2026
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