AI agents invoke apply_measure to trigger actions in Openstudio. 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.
In OpenStudio, 'measures' are scripts (typically Ruby or Python) that modify energy models or run simulations. 'apply_measure' almost certainly executes a measure script against a model, which constitutes running code with potential side effects including model modification. The description is empty, which lowers confidence, but the OpenStudio domain context strongly implies code/script execution.
From the tool's definition Tool name 'apply_measure' in context of OpenStudio building energy simulation server that supports 'running EnergyPlus simulations' and 'modification of models'
Documented attack patterns abuse exactly the kind of access apply_measure gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Openstudio, and nothing reaches the server without passing your rules. This is the rule we recommend for apply_measure:
{
"version": "1",
"default": "deny",
"tools": {
"apply_measure": {
"limits": [
{
"counter": "apply_measure_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
}apply_measure 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.
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apply_measure. It is categorised as a Execute tool in the Openstudio MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Openstudio MCP server in PolicyLayer and add a rule for apply_measure: 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 Openstudio. Nothing to install.
apply_measure is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.
Yes. Add a rate_limit block to the apply_measure 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 apply_measure. 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.
apply_measure is provided by the Openstudio MCP server (natlabrockies/openstudio-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Openstudio, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
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146 Openstudio tools catalogued and risk-classified — across an index of 43,000+ MCP servers.