AI agents invoke scatter_props to trigger actions in Uefn. 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.
Based on the tool name 'scatter_props' in the context of a UEFN editor bridge, this likely places/scatters prop actors across a scene, which constitutes triggering an external operation (modifying the live editor scene). Sibling tools like 'audio_place' suggest placement operations are common on this server.
From the tool's definition Tool name is 'scatter_props' on a UEFN (Unreal Editor for Fortnite) MCP server. Description is empty and uninformative.
Documented attack patterns abuse exactly the kind of access scatter_props gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Uefn, and nothing reaches the server without passing your rules. This is the rule we recommend for scatter_props:
{
"version": "1",
"default": "deny",
"tools": {
"scatter_props": {
"limits": [
{
"counter": "scatter_props_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
}scatter_props 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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scatter_props. It is categorised as a Execute tool in the Uefn MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Uefn MCP server in PolicyLayer and add a rule for scatter_props: 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 Uefn. Nothing to install.
scatter_props 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 scatter_props 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 scatter_props. 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.
scatter_props is provided by the Uefn MCP server (quangdang46/uefn-verse-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Uefn, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
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