Clear the cart
AI agents call clear_cart to permanently remove resources in FakeStore MCP — typically in cleanup and lifecycle workflows. It does its job in a single call, and there is no undo.
Clearing a cart removes all items irreversibly in a single operation with no indication of undo capability. This is a bulk destructive action — potentially losing all shopping intent for a user session — making it Destructive with high severity due to the blast radius of losing an entire cart's contents without item-by-item control.
From the tool's definition Tool name 'clear_cart' and description 'Clear the cart' indicate all items are removed from the cart at once.
Attacks that exploit this kind of access
Clear the cart. It is categorised as a Destructive tool in the FakeStore MCP MCP Server, which means it can permanently delete or destroy data. Block by default and require explicit approval.
Register the FakeStore MCP server in PolicyLayer and add a rule for clear_cart: 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 FakeStore MCP. Nothing to install.
clear_cart is a Destructive tool with critical risk. Critical-risk tools should be blocked by default and only enabled with explicit human approval.
Yes. Add a rate_limit block to the clear_cart 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 clear_cart. 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.
clear_cart is provided by the FakeStore MCP server (mithgroth/fakestore-mcp). 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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