auto_range

Optimise the input stage for the present signal: SR830 Auto Reserve (ARSV) or SR86x

SERVERPypi:labmcp Alicat SOURCEpypi:labmcp-alicat

High RISK CLASS

Category Execute

Parameters 00 required

Recommended Rate-limitedsee the rule below

Registry record Grade F, identity unverified Pull the record →

This record as markdown: /tools/lab-instrument-mcps/auto-range.md

WHAT IT DOES

What auto_range does on Pypi:labmcp Alicat

AI agents invoke auto_range to trigger actions in Pypi:labmcp Alicat. What it does depends on the arguments the agent supplies, and its effects often reach beyond the immediate call: builds kicked off, notifications sent, workflows started.

RISK

Why auto_range is rated High

Triggers automatic hardware adjustment of instrument settings, an external operation with real effects.

From the tool's definition Optimise the input stage for the present signal

Attacks that exploit this kind of access

RECOMMENDED RULE

The rule that runs auto_range 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 auto_range, this is the rule to start with:

auto_range Rate-limited

auto_range stays usable, but rate-capped: a runaway agent can't fire it dozens of times a minute. Everything else on the server is denied unless you say otherwise.

View as policy code

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "auto_range": {
      "limits": [
        {
          "counter": "auto_range_rate",
          "window": "minute",
          "max": 10,
          "scope": "grant"
        }
      ]
    }
  }
}

RATE-LIMIT 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 auto_range call is checked against it from then on.

FAQ

Questions about auto_range

What does the auto_range tool do? +

Optimise the input stage for the present signal: SR830 Auto Reserve (ARSV) or SR86x. It is categorised as a Execute tool in the Pypi:labmcp Alicat MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.

How do I enforce a policy on auto_range? +

Register the Pypi:labmcp Alicat MCP server in PolicyLayer and add a rule for auto_range: 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 auto_range? +

auto_range is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.

Can I rate-limit auto_range? +

Yes. Add a rate_limit block to the auto_range 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 auto_range completely? +

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

auto_range 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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