enable_watchdog

A execute tool on the Pypi:labmcp Alicat MCP server.

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/enable-watchdog.md

WHAT IT DOES

What enable_watchdog does on Pypi:labmcp Alicat

AI agents invoke enable_watchdog 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 enable_watchdog is rated High

Watchdog enabling likely triggers timed safety or control operations on lab instruments.

From the tool's definition uninformative description

Attacks that exploit this kind of access

RECOMMENDED RULE

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

enable_watchdog Rate-limited

enable_watchdog 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": {
    "enable_watchdog": {
      "limits": [
        {
          "counter": "enable_watchdog_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 enable_watchdog call is checked against it from then on.

FAQ

Questions about enable_watchdog

What does the enable_watchdog tool do? +

enable_watchdog is a execute tool on the Pypi:labmcp Alicat MCP server. 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 enable_watchdog? +

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

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

Can I rate-limit enable_watchdog? +

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

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

enable_watchdog 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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