AI agents use config_set to create or update resources in Uefn — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Uefn environment.
The 'config_set' tool modifies configuration state in the Unreal Editor for Fortnite, making it a Write operation. While the description is empty (reducing confidence), the name pattern and server context (a tool suite for driving a live editor) strongly indicate this creates or modifies configuration data.
From the tool's definition Tool name 'config_set' indicates setting/modifying configuration. Context shows this is part of a UEFN editor control system with sibling tools like 'actor_move_to_folder', 'actor_set_label', etc. that are clearly modification operations.
Documented attack patterns abuse exactly the kind of access config_set 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 config_set:
{
"version": "1",
"default": "deny",
"tools": {
"config_set": {
"limits": [
{
"counter": "config_set_rate",
"window": "minute",
"max": 30,
"scope": "grant"
}
]
}
}
}config_set stays usable, but capped — an agent stuck in a loop can't make hundreds of changes a minute. Everything else on the server is denied unless you say otherwise.
Free to start. No card required.
config_set. It is categorised as a Write tool in the Uefn MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Uefn MCP server in PolicyLayer and add a rule for config_set: 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.
config_set is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.
Yes. Add a rate_limit block to the config_set 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 config_set. 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.
config_set 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.
Free to start. No card required.
143 Uefn tools catalogued and risk-classified — across an index of 43,000+ MCP servers.