list_runs
List recent protocol runs, newest first, with their status.
This record as markdown: /tools/lab-instrument-mcps/list-runs.md
What list_runs does on Pypi:labmcp Alicat
AI agents call list_runs 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.
Why list_runs is rated Low
Tool retrieves historical protocol run data without modifying or executing anything.
From the tool's definition List recent protocol runs with their status; read-only query operation.
Attacks that exploit this kind of access
The rule that runs list_runs 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 list_runs, this is the rule to start with:
list_runs is read-only, so it stays allowed. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect Pypi:labmcp Alicat, apply this rule, and every list_runs call is checked against it from then on.
Questions about list_runs
List recent protocol runs, newest first, with their status. It is categorised as a Read tool in the Pypi:labmcp Alicat MCP Server, which means it retrieves data without modifying state.
Register the Pypi:labmcp Alicat MCP server in PolicyLayer and add a rule for list_runs: 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.
list_runs is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the list_runs 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.
Set action: deny in the PolicyLayer policy for list_runs. 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.
list_runs 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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