AI agents invoke reveal_in_finder to trigger actions in Mac. 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.
This tool triggers an external application (Finder) and performs a UI action (revealing/selecting a file or folder). While it doesn't modify or delete data, it executes an operation that interacts with the macOS system and UI, making it Execute rather than Read. Misuse could expose sensitive file paths or locations to view.
From the tool's definition Opens Finder and selects the specified file or folder
Attacks that exploit this kind of access
Opens Finder and selects the specified file or folder. It is categorised as a Execute tool in the Mac MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Mac MCP server in PolicyLayer and add a rule for reveal_in_finder: 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 Mac. Nothing to install.
reveal_in_finder 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 reveal_in_finder 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 reveal_in_finder. 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.
reveal_in_finder is provided by the Mac MCP server (laststance/mac-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Every MCP server has a record like this.
Type a name, get the same breakdown: verified identity, auth posture, risk grade, capabilities, recommended policy.
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