AI agents call list-favorites to retrieve information from MCP Prompt Manager 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-only operation that retrieves a list of favorited prompts from local storage. No data is created, modified, deleted, or executed. The operation has no side effects and poses minimal security risk even if misused by an AI agent, as it only exposes information about which prompts the user has marked as favorites.
From the tool's definition The tool name is 'list-favorites' and the description states it 'List all favorite prompts'. This operation retrieves or queries data without modifying, deleting, or executing anything.
Documented attack patterns abuse exactly the kind of access list-favorites gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and MCP Prompt Manager, and nothing reaches the server without passing your rules. This is the rule we recommend for list-favorites:
{
"version": "1",
"default": "deny",
"tools": {
"list-favorites": {}
}
}list-favorites is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.
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List all favorite prompts. It is categorised as a Read tool in the MCP Prompt Manager MCP Server, which means it retrieves data without modifying state.
Register the MCP Prompt Manager MCP server in PolicyLayer and add a rule for list-favorites: 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 MCP Prompt Manager. Nothing to install.
list-favorites 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-favorites 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-favorites. 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-favorites is provided by the MCP Prompt Manager MCP server (tae4an/mcp-prompt-manager). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from MCP Prompt Manager, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
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33 MCP Prompt Manager tools catalogued and risk-classified — across an index of 43,000+ MCP servers.