nefesh-mcp-server
The Nefesh MCP Server gives AI agents real-time awareness of human physiological and emotional states, enabling adaptive, context-aware behavior based on biometric and behavioral signals.
Get Human State (
get_human_state): Retrieve the current unified stress state (calm/relaxed/focused/stressed/acute_stress), a stress score (0–100), a confidence rating, and a suggested machine-readable action (e.g.,maintain_engagement,simplify_and_focus,de-escalate_and_shorten,pause_and_ground). On the 2nd+ call, also receive adaptation effectiveness feedback showing whether the previous action reduced or worsened stress (stress_deltaandeffectiveboolean).Ingest Biometric Signals (
ingest): Send 30+ sensor signals (heart rate, HRV/RMSSD, EDA, SpO2, EEG bands, vocal tone, facial expression, text sentiment, glucose, respiratory rate, sleep stage, etc.) and receive a fused unified human state in return. Includingsubject_id,user_message, andai_responseenables cross-session trigger memory tracking.Get Trigger Memory (
get_trigger_memory): Retrieve a cross-session psychological trigger profile identifying which conversation topics consistently cause stress (active triggers) vs. those resolved over time, with observation counts, average/peak scores, and timestamps.Get Session History (
get_session_history): Fetch a timestamped history of stress scores, states, and heart rate readings for a session, with a configurable lookback window (up to 60 minutes) and an overall trend indicator (rising/falling/stable).Autonomous API Provisioning: AI agents can self-provision free API keys (1,000 calls/month, no credit card required) via email verification without manual signup.
Multi-Protocol Support: Works with both Model Context Protocol (MCP) for tool-calling and Agent-to-Agent (A2A) protocol for peer-to-peer communication.
Privacy-Focused: Edge processing with no video/audio uploads; GDPR/BIPA compliant with cascading deletion capabilities.
Enables Amazon Kiro to access real-time human physiological state data, stress scores, and adaptation effectiveness feedback for context-aware AI interactions.
Integrates with the Windsurf editor to provide AI agents with unified human state awareness, including stress levels and suggested actions for response adaptation.
Allows AI agents within JetBrains IDEs to query human physiological state, track psychological triggers, and adapt interactions based on stress scores and session history.
Enables the OpenAI Codex CLI to ingest biometric signals and retrieve human state data with adaptation effectiveness metrics for stress-aware coding assistance.
Integrates with Replit to provide physiological state awareness and trigger memory capabilities to agents running in Replit environments.
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:
"Connect to Nefesh and get me a free API key for name@example.com"
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
Agent | Config file |
Cursor |
|
Windsurf |
|
Claude Desktop |
|
Claude Code |
|
VS Code (Copilot) |
|
Cline |
|
Continue.dev |
|
Roo Code |
|
Kiro (Amazon) |
|
OpenClaw |
|
JetBrains IDEs | Settings > Tools > MCP Server |
Zed |
|
OpenAI Codex CLI |
|
Goose CLI |
|
ChatGPT Desktop | Settings > Apps > Add MCP Server (UI) |
Gemini CLI | Settings (UI) |
Augment | Settings Panel (UI) |
Replit | Integrations Page (web UI) |
LibreChat |
|
{
"servers": {
"nefesh": {
"type": "http",
"url": "https://mcp.nefesh.ai/mcp",
"headers": {
"X-Nefesh-Key": "<YOUR_API_KEY>"
}
}
}
}{
"context_servers": {
"nefesh": {
"settings": {
"url": "https://mcp.nefesh.ai/mcp",
"headers": {
"X-Nefesh-Key": "<YOUR_API_KEY>"
}
}
}
}
}[mcp_servers.nefesh]
url = "https://mcp.nefesh.ai/mcp"mcpServers:
- name: nefesh
type: streamable-http
url: https://mcp.nefesh.ai/mcpAll 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 Skill | Description |
| Stress state (0-100), suggested_action, adaptation_effectiveness |
| Send biometric signals, receive unified state |
| Psychological trigger profile (active vs resolved) |
| Timestamped 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
Tool | Auth | Description |
| No | Request a free API key by email. Poll with |
| No | Poll for API key activation. Returns |
| Yes | Get stress state (0-100), |
| Yes | Send biometric signals (heart rate, HRV, voice tone, expression, sentiment, 30+ fields) and get unified state back. Include |
| Yes | Get psychological trigger profile — which topics cause stress (active) and which have been resolved over time. |
| Yes | Get 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.
Agent calls
request_api_key(email)— no API key needed for this callYou receive a verification email and click the link
Agent polls
check_api_key_status(request_id)every 10 secondsOnce verified, the agent receives the API key and can use all other tools
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
Plan | Price | API Calls |
Free | $0 | 1,000/month, no credit card |
Solo | $25/month | 50,000/month |
Enterprise | Custom | Custom 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 --jsonGitHub: 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
Privacy
No video or audio uploads — edge processing runs client-side
No PII stored
GDPR/BIPA compliant — cascading deletion via
delete_subjectNot a medical device — for contextual AI adaptation only
License
MIT — see LICENSE.
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