AI agents call get_item to retrieve information from Wardrowbe without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool retrieves a single wardrobe item by identifier. It has no side effects, does not modify data, and poses minimal risk if misused by an AI agent—at worst, it reveals information about a user's wardrobe item. This is a straightforward Read category tool.
From the tool's definition Tool name 'get_item' and description 'Fetch a single item by id' indicate data retrieval with no modification or deletion. 'Fetch' is explicitly a read operation.
Attacks that exploit this kind of access
Fetch a single item by id. It is categorised as a Read tool in the Wardrowbe MCP Server, which means it retrieves data without modifying state.
Register the Wardrowbe MCP server in PolicyLayer and add a rule for get_item: 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 Wardrowbe. Nothing to install.
get_item is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the get_item 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 get_item. 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.
get_item is provided by the Wardrowbe MCP server (saya6k/mcp-wardrowbe). 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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