Low Risk

get_human_state

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) - sugges...

Part of the Human State MCP server. Enforce policies on this tool with Intercept, the open-source MCP proxy.

AI agents call get_human_state to retrieve information from Human State without modifying any data. This is common in research, monitoring, and reporting workflows where the agent needs context before taking action. Because read operations don't change state, they are generally safe to allow without restrictions -- but you may still want rate limits to control API costs.

Even though get_human_state only reads data, uncontrolled read access can leak sensitive information or rack up API costs. An agent caught in a retry loop could make thousands of calls per minute. A rate limit gives you a safety net without blocking legitimate use.

Read-only tools are safe to allow by default. No rate limit needed unless you want to control costs.

nefesh-ai-human-state.yaml
tools:
  get_human_state:
    rules:
      - action: allow

See the full Human State policy for all 6 tools.

Tool Name get_human_state
Category Read
Risk Level Low

Agents calling read-class tools like get_human_state have been implicated in these attack patterns. Read the full case and prevention policy for each:

Browse the full MCP Attack Database →

Other tools in the Read risk category across the catalogue. The same policy patterns (rate-limit, allow) apply to each.

What does the get_human_state tool do? +

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) - 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. . It is categorised as a Read tool in the Human State MCP Server, which means it retrieves data without modifying state.

How do I enforce a policy on get_human_state? +

Add a rule in your Intercept YAML policy under the tools section for get_human_state. You can allow, deny, rate-limit, or validate arguments. Then run Intercept as a proxy in front of the Human State MCP server.

What risk level is get_human_state? +

get_human_state is a Read tool with low risk. Read-only tools are generally safe to allow by default.

Can I rate-limit get_human_state? +

Yes. Add a rate_limit block to the get_human_state rule in your Intercept policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.

How do I block get_human_state completely? +

Set action: deny in the Intercept policy for get_human_state. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.

What MCP server provides get_human_state? +

get_human_state is provided by the Human State MCP server (nefesh-ai/human-state). Intercept sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policies on Human State

Open source. One binary. Zero dependencies.

npx -y @policylayer/intercept
github.com/policylayer/intercept →
// GET IN TOUCH

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