Present choices to the player with multi-select and free-form input support. Returns structured choice data for the DM agent to display.
AI agents call present_choices to retrieve information from DMCP without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool retrieves and formats choice options for display to the player. It has no side effects on game data, does not execute code or commands, does not modify or delete data, and does not involve financial transactions. It is purely a data presentation mechanism that reads game state to construct UI choices, making it a Read category tool with low severity.
From the tool's definition Tool description states it 'Present choices to the player' and 'Returns structured choice data for the DM agent to display.' The verb 'present' and 'returns' indicate data retrieval and formatting, with no modification of game state, deletion, or external…
Documented attack patterns abuse exactly the kind of access present_choices gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and DMCP, and nothing reaches the server without passing your rules. This is the rule we recommend for present_choices:
{
"version": "1",
"default": "deny",
"tools": {
"present_choices": {}
}
}present_choices is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.
Free to start. No card required.
Present choices to the player with multi-select and free-form input support. Returns structured choice data for the DM agent to display. It is categorised as a Read tool in the DMCP MCP Server, which means it retrieves data without modifying state.
Register the D MCP server in PolicyLayer and add a rule for present_choices: 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 DMCP. Nothing to install.
present_choices 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 present_choices 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 present_choices. 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.
present_choices is provided by the D MCP server (shawnrushefsky/dmcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from DMCP, 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.
204 DMCP tools catalogued and risk-classified — across an index of 43,000+ MCP servers.