Basket analysis — frequently bought together products.
AI agents call basket_analysis to retrieve information from AdminAgent without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool performs analytical queries to identify product associations (frequently bought together), which is a read-only operation retrieving and analyzing existing sales data without modifying any state.
From the tool's definition Basket analysis — frequently bought together products
Attacks that exploit this kind of access
Basket analysis — frequently bought together products. It is categorised as a Read tool in the AdminAgent MCP Server, which means it retrieves data without modifying state.
Register the AdminAgent MCP server in PolicyLayer and add a rule for basket_analysis: 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 AdminAgent. Nothing to install.
basket_analysis 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 basket_analysis 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 basket_analysis. 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.
basket_analysis is provided by the AdminAgent MCP server (rushikeshmore/admin-agent). 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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