This record as markdown: /tools/jjpxdev-unreal-mcp/clean-project.md
What clean_project does on Unreal
AI agents invoke clean_project to trigger actions in Unreal. 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.
| Parameter | Type | Required | Description |
|---|---|---|---|
platform | string | — | Target platform |
Parameters from the server's own tool schema.
Why clean_project is rated High
This tool runs an external build cleanup operation whose effects depend on the project state and configuration. While not immediately destructive (build artifacts can often be regenerated), it is an Execute action because it triggers automated processes outside direct control and can have wide side effects on the development environment.
From the tool's definition 'Clean build artifacts for the project' — executes a build system operation that triggers external processes and modifies the project's build directory structure, potentially affecting multiple dependent systems.
Attacks that exploit this kind of access
The rule that runs clean_project 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 clean_project, this is the rule to start with:
clean_project 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.
The button opens the PolicyLayer dashboard: create your workspace, connect Unreal, apply this rule, and every clean_project call is checked against it from then on.
Questions about clean_project
Clean build artifacts for the project. It is categorised as a Execute tool in the Unreal MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
clean_project accepts 1 parameter: platform. The full parameter table on this page comes from the server's own tool schema.
Register the Unreal MCP server in PolicyLayer and add a rule for clean_project: 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.
clean_project 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 clean_project 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 clean_project. 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.
clean_project 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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