AI agents use set_rules 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 is a Write operation—it persists rule data to game state. Severity is medium because misuse could corrupt game mechanics or create unfair gameplay conditions, but the blast radius is limited to a single game instance and is reversible (rules can be updated/replaced). Not Destructive since rules can be overwritten, not permanently deleted. Not Execute since it stores data rather than triggering external code.
From the tool's definition The tool 'set_rules' with description 'Store a rule system for the game' creates or modifies game state by persisting rule configuration data. 'Store' indicates data creation/modification rather than retrieval.
Documented attack patterns abuse exactly the kind of access set_rules 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 set_rules:
{
"version": "1",
"default": "deny",
"tools": {
"set_rules": {
"limits": [
{
"counter": "set_rules_rate",
"window": "minute",
"max": 30,
"scope": "grant"
}
]
}
}
} set_rules 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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Store a rule system for the game. 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 set_rules: 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.
set_rules 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 set_rules 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 set_rules. 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.
set_rules 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.
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204 DMCP tools catalogued and risk-classified — across an index of 43,000+ MCP servers.