This record as markdown: /tools/quangdang46-uefn-verse-mcp/bulk-mirror.md
What bulk_mirror does on Uefn
AI agents invoke bulk_mirror 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.
Why bulk_mirror is rated High
Based on sibling tools (actor_move_to_folder, actor_set_label, actor_hide, etc.), this server drives a live UEFN editor. 'bulk_mirror' likely mirrors/reflects multiple actors in the scene — a Write or Execute operation. Given the empty description, confidence is low.
From the tool's definition Tool name 'bulk_mirror' with empty description. The word 'bulk' suggests batch operations on multiple items, and 'mirror' suggests transformation/reflection operations in a 3D editor context.
Risk signalsBulk/mass operation — affects multiple targets
Attacks that exploit this kind of access
The rule that runs bulk_mirror safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Uefn, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For bulk_mirror, this is the rule to start with:
bulk_mirror 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 Uefn, apply this rule, and every bulk_mirror call is checked against it from then on.
Questions about bulk_mirror
bulk_mirror is a execute tool on the Uefn MCP server. 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 bulk_mirror: 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.
bulk_mirror 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 bulk_mirror 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 bulk_mirror. 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.
bulk_mirror 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.
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