get_results

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

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-results.md

WHAT IT DOES

What get_results does on Pypi:labmcp Alicat

AI agents call get_results 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_results is rated Low

The tool appears to query and return results from the research table system. Despite the empty description, the pattern of read-oriented 'get_' prefixed tools in the server and the overall context of 'viewing' research outputs (as opposed to modify/delete/execute tools like add_validated_rows, exclude_row, approve_validation) indicates a retrieval operation with no data modification or external execution.

From the tool's definition Tool name 'get_results' indicates data retrieval. Empty description limits certainty, but naming convention and sibling tools (discover_rows, get_preview_state, get_job_status) that clearly retrieve state/data suggest this retrieves cached or generated…

Attacks that exploit this kind of access

RECOMMENDED RULE

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

get_results Allowed

get_results 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_results": {}
  }
}

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_results call is checked against it from then on.

FAQ

Questions about get_results

What does the get_results tool do? +

get_results is a read tool on the Pypi:labmcp Alicat MCP server. 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_results? +

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

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

Can I rate-limit get_results? +

Yes. Add a rate_limit block to the get_results 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_results completely? +

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

get_results 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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