AI agents invoke set_active_view to trigger actions in GOLEM-3DMCP-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.
This tool changes the active viewport in Rhino, which is an external application state change. While not destructive or data-modifying in a traditional sense, it triggers an operation in an external tool (Rhino), classifying it as Execute. The blast radius is low since it only affects which viewport is currently active and does not modify geometry or data.
From the tool's definition 'Set the active Rhino viewport by name' — triggers an external operation within Rhino that changes application state
Documented attack patterns abuse exactly the kind of access set_active_view gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and GOLEM-3DMCP-Rhino-, and nothing reaches the server without passing your rules. This is the rule we recommend for set_active_view:
{
"version": "1",
"default": "deny",
"tools": {
"set_active_view": {
"limits": [
{
"counter": "set_active_view_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
}set_active_view 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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Set the active Rhino viewport by name. It is categorised as a Execute tool in the GOLEM-3DMCP-Rhino- MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the GOLEM-3DMCP-Rhino- MCP server in PolicyLayer and add a rule for set_active_view: 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 GOLEM-3DMCP-Rhino-. Nothing to install.
set_active_view 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 set_active_view 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 set_active_view. 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.
set_active_view is provided by the GOLEM-3DMCP-Rhino- MCP server (thekinghippopotamus/golem-3dmcp-rhino-). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from GOLEM-3DMCP-Rhino-, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
Free to start. No card required.
89 GOLEM-3DMCP-Rhino- tools catalogued and risk-classified — across an index of 43,000+ MCP servers.