Advance time by a duration, returning any triggered scheduled events
AI agents use advance_time to create or update resources in DMCP — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your DMCP environment.
This tool modifies game state by advancing the in-game time and triggering scheduled events. It creates/modifies data within the RPG game state (reversible in a game context). No code execution, deletion, or financial operations involved. Blast radius is low as it only affects a text-based RPG game state.
From the tool's definition Advance time by a duration, returning any triggered scheduled events
Documented attack patterns abuse exactly the kind of access advance_time 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 advance_time:
{
"version": "1",
"default": "deny",
"tools": {
"advance_time": {
"limits": [
{
"counter": "advance_time_rate",
"window": "minute",
"max": 30,
"scope": "grant"
}
]
}
}
}advance_time stays usable, but capped — an agent stuck in a loop can't make hundreds of changes a minute. Everything else on the server is denied unless you say otherwise.
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Advance time by a duration, returning any triggered scheduled events. It is categorised as a Write tool in the DMCP MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the D MCP server in PolicyLayer and add a rule for advance_time: 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.
advance_time is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.
Yes. Add a rate_limit block to the advance_time 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 advance_time. 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.
advance_time 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.
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