get_command_result

Responses of a finished observable command, or the SiLA execution error it finished with.

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/get-command-result.md

WHAT IT DOES

What get_command_result does on Pypi:labmcp Alicat

AI agents call get_command_result 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 get_command_result is rated Low

Tool retrieves results from already-completed commands without side effects or new operations.

From the tool's definition Responses of finished observable command, execution error it finished with

Attacks that exploit this kind of access

RECOMMENDED RULE

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

get_command_result Allowed

get_command_result 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": {
    "get_command_result": {}
  }
}

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 get_command_result call is checked against it from then on.

FAQ

Questions about get_command_result

What does the get_command_result tool do? +

Responses of a finished observable command, or the SiLA execution error it finished with. 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 get_command_result? +

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

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

Can I rate-limit get_command_result? +

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

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

get_command_result 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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