AI agents invoke run_tool 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.
The name 'run_tool' in an MCP context that bridges to a live Unreal editor indicates code/tool execution capability. Although the description is empty (reducing confidence slightly), the function name and server purpose indicate this tool triggers external operations whose effects depend on arguments—classic Execute category behavior.
From the tool's definition Tool name is 'run_tool' with empty description. In the context of a UEFN (Unreal Editor for Fortnite) MCP bridge, 'run_tool' strongly suggests execution of arbitrary tools or scripts within the editor environment.
Documented attack patterns abuse exactly the kind of access run_tool 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 run_tool:
{
"version": "1",
"default": "deny",
"tools": {
"run_tool": {
"limits": [
{
"counter": "run_tool_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
}run_tool 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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run_tool. 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 run_tool: 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.
run_tool 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 run_tool 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 run_tool. 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.
run_tool 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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143 Uefn tools catalogued and risk-classified — across an index of 43,000+ MCP servers.