STEP 2: Get Agentforce AI recommendations and full product details. Call this AFTER search-target-products to receive personalized recommendations based on customer purchase history and complete product information for the search results.
AI agents call get-agentforce-recommendations to retrieve information from ChatGPT Interactive Components Examples without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool retrieves product recommendations and details based on existing customer history and prior search results. It performs a lookup/query operation without creating, modifying, deleting, or executing external code. Even though it may access customer purchase history (potentially sensitive), the operation itself is purely informational retrieval with no destructive or reversible state changes.
From the tool's definition Tool description states it 'receives personalized recommendations' and 'complete product information' - both retrieval operations with no modification or side effects.
Attacks that exploit this kind of access
STEP 2: Get Agentforce AI recommendations and full product details. Call this AFTER search-target-products to receive personalized recommendations based on customer purchase history and complete product information for the search results. It is categorised as a Read tool in the ChatGPT Interactive Components Examples MCP Server, which means it retrieves data without modifying state.
Register the ChatGPT Interactive Components Examples MCP server in PolicyLayer and add a rule for get-agentforce-recommendations: 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 ChatGPT Interactive Components Examples. Nothing to install.
get-agentforce-recommendations 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-agentforce-recommendations 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-agentforce-recommendations. 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-agentforce-recommendations is provided by the ChatGPT Interactive Components Examples MCP server (skyrmionz/chatgpt-mcp-server-interactive-components). 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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