Add item to user
AI agents use add_to_cart to create or update resources in FakeStore MCP — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your FakeStore MCP environment.
Adding items to a cart modifies user state (the cart contents) but is reversible—items can be removed via remove_from_cart or the cart can be cleared via clear_cart. This is a classic Write operation: it creates or modifies data without permanent deletion.
From the tool's definition Tool name 'add_to_cart' and description 'Add item to user' indicate creation/modification of shopping cart state. This is a write operation that creates or modifies cart data reversibly.
Attacks that exploit this kind of access
Add item to user. It is categorised as a Write tool in the FakeStore MCP MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the FakeStore MCP server in PolicyLayer and add a rule for add_to_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.
add_to_cart 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 add_to_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 add_to_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.
add_to_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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