resume_control

Cancel any valve hold and resume closed-loop control to the current setpoint. Flow restarts

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/resume-control.md

WHAT IT DOES

What resume_control does on Pypi:labmcp Alicat

AI agents invoke resume_control 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 resume_control is rated High

Resumes physical instrument control and restarts flow, triggering real-world equipment operation.

From the tool's definition Cancel any valve hold and resume closed-loop control, Flow restarts

Attacks that exploit this kind of access

RECOMMENDED RULE

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

resume_control Rate-limited

resume_control 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": {
    "resume_control": {
      "limits": [
        {
          "counter": "resume_control_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 resume_control call is checked against it from then on.

FAQ

Questions about resume_control

What does the resume_control tool do? +

Cancel any valve hold and resume closed-loop control to the current setpoint. Flow restarts. 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 resume_control? +

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

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

Can I rate-limit resume_control? +

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

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

resume_control 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.

KEEP EXPLORING

More on Pypi:labmcp Alicat, and thousands of servers like it.

This server

All 242 Pypi:labmcp Alicat tools → High-risk tools on this server →

Across the catalogue

resume on Frida Game Hacking MCP → All high-risk MCP tools → The MCP Attack Database →

Guides

Govern code and CI agents →Agent sandbox →Least privilege for MCP →