Check if user has completed icon selection in web interface. This tool will wait for user selection and return selected icons when completed.
AI agents call check_selection_status to retrieve information from Icon without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool performs a read operation by retrieving the status of user selections from the web interface. It has no side effects, does not modify data, and does not trigger external operations with unpredictable effects. The worst-case misuse scenario is checking selection status repeatedly, which poses minimal risk. Therefore, it is classified as Read with low severity.
From the tool's definition Tool 'check_selection_status' checks and waits for user input, returning selected icons when completed. The description indicates it retrieves the status of user selections without modifying any data: 'Check if user has completed icon selection...
Documented attack patterns abuse exactly the kind of access check_selection_status gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Icon, and nothing reaches the server without passing your rules. This is the rule we recommend for check_selection_status:
{
"version": "1",
"default": "deny",
"tools": {
"check_selection_status": {}
}
}check_selection_status is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.
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Check if user has completed icon selection in web interface. This tool will wait for user selection and return selected icons when completed. It is categorised as a Read tool in the Icon MCP Server, which means it retrieves data without modifying state.
Register the Icon MCP server in PolicyLayer and add a rule for check_selection_status: 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 Icon. Nothing to install.
check_selection_status 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 check_selection_status 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 check_selection_status. 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.
check_selection_status is provided by the Icon MCP server (liliangshan/mcp-server-icon). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Icon, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
Free to start. No card required.
5 Icon tools catalogued and risk-classified — across an index of 43,000+ MCP servers.