This record as markdown: /tools/easehee-rhino-mcp/rhino-object-select.md
What rhino_object_select does on Rhino
AI agents invoke rhino_object_select to trigger actions in Rhino. 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.
Why rhino_object_select is rated High
Based on the tool name, this likely selects objects within Rhino 8, which would be a UI/state-change action (triggering an external operation in the Rhino environment). Selecting objects can have downstream effects (e.g., subsequent operations act on the selection). However, with no description available, confidence is low.
From the tool's definition Tool name 'rhino_object_select' — description is empty and uninformative.
Attacks that exploit this kind of access
The rule that runs rhino_object_select safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Rhino, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For rhino_object_select, this is the rule to start with:
rhino_object_select 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.
The button opens the PolicyLayer dashboard: create your workspace, connect Rhino, apply this rule, and every rhino_object_select call is checked against it from then on.
Questions about rhino_object_select
rhino_object_select is a execute tool on the Rhino MCP server. It is categorised as a Execute tool in the Rhino MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Rhino MCP server in PolicyLayer and add a rule for rhino_object_select: 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 Rhino. Nothing to install.
rhino_object_select 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 rhino_object_select 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 rhino_object_select. 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.
rhino_object_select is provided by the Rhino MCP server (easehee/rhino-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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