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Fuses biometric signals into a stress score (0-100) for AI adaptation. MCP + A2A native.
About
Fuses biometric signals into a stress score (0-100) for AI adaptation. MCP + A2A native.
Remote endpoints: streamable-http: https://mcp.nefesh.ai/mcp
Security Report
This server has significant security concerns including missing authentication mechanisms and potential exposure of user credentials. While it functions as a proxy to the Nefesh API, it lacks proper authentication implementation for production use and contains concerning patterns in credential handling. Supply chain analysis found 5 known vulnerabilities in dependencies (1 critical, 3 high severity).
3 files analyzed · 10 issues found
Security scores are indicators to help you make informed decisions, not guarantees. Always review permissions before connecting any MCP server.
Permissions Required
This plugin requests these system permissions. Most are normal for its category.
Unverified package source
We couldn't verify that the installable package matches the reviewed source code. Proceed with caution.
How to Install & Connect
Available as Local & Remote
This plugin can run on your machine or connect to a hosted endpoint. during install.
Documentation
View on GitHubFrom the project's GitHub README.
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
| Agent | Config 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 |
| Cline | cline_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 IDEs | Settings > Tools > MCP Server |
| Zed | ~/.config/zed/settings.json (uses context_servers) |
| OpenAI Codex CLI | ~/.codex/config.toml |
| Goose CLI | ~/.config/goose/config.yaml |
| ChatGPT Desktop | Settings > Apps > Add MCP Server (UI) |
| Gemini CLI | Settings (UI) |
| Augment | Settings Panel (UI) |
| Replit | Integrations Page (web UI) |
| LibreChat | librechat.yaml (self-hosted) |
{
"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/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 Skill | Description |
|---|---|
get-human-state | Stress state (0-100), suggested_action, adaptation_effectiveness |
ingest-signals | Send biometric signals, receive unified state |
get-trigger-memory | Psychological trigger profile (active vs resolved) |
get-session-history | 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 |
|---|---|---|
request_api_key | No | Request 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_status | No | Poll for API key activation using the same email the user provided. Returns pending or ready with API key. |
get_human_state | Yes | Get stress state (0-100), suggested_action (maintain/simplify/de-escalate/pause), and adaptation_effectiveness — a closed-loop showing whether your previous action reduced stress. |
ingest | Yes | Send biometric signals (heart rate, HRV, voice tone, expression, sentiment, 30+ fields) and get unified state back. Include subject_id for trigger memory. |
get_trigger_memory | Yes | Get psychological trigger profile — which topics cause stress (active) and which have been resolved over time. |
get_session_history | 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 asks you: "What is your email address?"
- Agent calls
request_api_key(your_real_email). No API key needed for this call. - You receive a verification email and click the link
- Agent polls
check_api_key_status(your_real_email)every 10 seconds - 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
| 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 --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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