This record as markdown: /tools/jjpxdev-unreal-mcp/redo.md
What redo does on Unreal
AI agents use redo to create or update resources in Unreal, usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Unreal environment.
Why redo is rated Medium
The redo operation re-applies a previously undone action in the Unreal Engine editor, thereby creating or restoring modifications to the project. This is a reversible write operation—an agent could redo changes that were intentionally undone, causing unintended modifications to assets, blueprints, or scene state.
From the tool's definition Tool name is 'redo' and description states 'Redo the last undone editor action.' This reverses an undo operation, which modifies the editor state and project contents.
Attacks that exploit this kind of access
The rule that runs redo safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Unreal, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For redo, this is the rule to start with:
redo 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.
The button opens the PolicyLayer dashboard: create your workspace, connect Unreal, apply this rule, and every redo call is checked against it from then on.
Questions about redo
Redo the last undone editor action. It is categorised as a Write tool in the Unreal MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Unreal MCP server in PolicyLayer and add a rule for redo: 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 Unreal. Nothing to install.
redo 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 redo 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 redo. 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.
redo is provided by the Unreal MCP server (@jjpxdev/unreal-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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