output_off

Switch a channel's output OFF. Safe to call at any time.

SERVERPypi:labmcp Alicat SOURCEpypi:labmcp-alicat

Low RISK CLASS

Category Read

Parameters 00 required

Recommended Allowedsee the rule below

Registry record Grade F, identity unverified Pull the record →

This record as markdown: /tools/lab-instrument-mcps/output-off.md

WHAT IT DOES

What output_off does on Pypi:labmcp Alicat

AI agents call output_off to retrieve information from Pypi:labmcp Alicat without modifying anything. It is typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.

RISK

Why output_off is rated Low

Even though output_off only reads data, uncontrolled read access leaks sensitive information and racks up API costs: an agent caught in a retry loop can make thousands of calls a minute without anyone noticing.

Attacks that exploit this kind of access

RECOMMENDED RULE

The rule that runs output_off safely

PolicyLayer is an MCP gateway: it sits between your AI agents and Pypi:labmcp Alicat, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For output_off, this is the rule to start with:

output_off Allowed

output_off is read-only, so it stays allowed. Everything else on the server is denied unless you say otherwise.

View as policy code

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "output_off": {}
  }
}

ALLOW ONLY THIS TOOL → Instant setup, no code required.

The button opens the PolicyLayer dashboard: create your workspace, connect Pypi:labmcp Alicat, apply this rule, and every output_off call is checked against it from then on.

FAQ

Questions about output_off

What does the output_off tool do? +

Switch a channel's output OFF. Safe to call at any time. It is categorised as a Read tool in the Pypi:labmcp Alicat MCP Server, which means it retrieves data without modifying state.

How do I enforce a policy on output_off? +

Register the Pypi:labmcp Alicat MCP server in PolicyLayer and add a rule for output_off: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches Pypi:labmcp Alicat. Nothing to install.

What risk level is output_off? +

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

Can I rate-limit output_off? +

Yes. Add a rate_limit block to the output_off rule in your PolicyLayer 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 output_off completely? +

Set action: deny in the PolicyLayer policy for output_off. 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 output_off? +

output_off is provided by the Pypi:labmcp Alicat MCP server (pypi:labmcp-alicat). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

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