AI agents call listModels to retrieve information from MongTap without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
Even though listModels only reads data, uncontrolled read access leaks sensitive information and racks up API costs — an agent caught in a retry loop can make thousands of calls a minute without anyone noticing.
Attacks that exploit this kind of access
Get a list of all available statistical models stored locally. It is categorised as a Read tool in the MongTap MCP Server, which means it retrieves data without modifying state.
Register the MongTap MCP server in PolicyLayer and add a rule for listModels: 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 MongTap. Nothing to install.
listModels 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 listModels 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 listModels. 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.
listModels is provided by the MongTap MCP server (smallmindsco/mongtap). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.