tare_flow

Tare (zero) the flow reading. ONLY run with no flow through the device: upstream shut off

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/tare-flow.md

WHAT IT DOES

What tare_flow does on Pypi:labmcp Alicat

AI agents invoke tare_flow 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 tare_flow is rated High

Calibrates instrument state; requires specific preconditions but can affect subsequent measurements if misused.

From the tool's definition Tare (zero) the flow reading, ONLY run with no flow

Attacks that exploit this kind of access

RECOMMENDED RULE

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

tare_flow Rate-limited

tare_flow 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": {
    "tare_flow": {
      "limits": [
        {
          "counter": "tare_flow_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 tare_flow call is checked against it from then on.

FAQ

Questions about tare_flow

What does the tare_flow tool do? +

Tare (zero) the flow reading. ONLY run with no flow through the device: upstream shut off. 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 tare_flow? +

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

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

Can I rate-limit tare_flow? +

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

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

tare_flow 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

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