AI agents call list_exams to retrieve information from Leafeep without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool retrieves and displays existing exam/question set data without creating, modifying, deleting, or executing any operations. It is a straightforward read operation with minimal risk; the only potential concern is information disclosure, but within an educator context using a quiz platform, listing exams is an expected low-risk administrative function.
From the tool's definition Tool name 'list_exams' and description 'List all your question sets' indicate a retrieval operation with no modification or side effects.
Attacks that exploit this kind of access
List all your question sets. It is categorised as a Read tool in the Leafeep MCP Server, which means it retrieves data without modifying state.
Register the Leafeep MCP server in PolicyLayer and add a rule for list_exams: 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 Leafeep. Nothing to install.
list_exams 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 list_exams 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 list_exams. 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.
list_exams is provided by the Leafeep MCP server (xhae123/leafeep-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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