AI agents use update_quest 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 creates or modifies quest data within the game state management system. While reversible (quests can be updated again), it affects the narrative and game progression. Classified as Write rather than Execute because it modifies specific game entities rather than executing arbitrary code or commands.
From the tool's definition Tool name 'update_quest' and description 'Update a quest' indicate modification of game state data. The context of a dungeon master RPG system confirms this modifies existing quest records.
Documented attack patterns abuse exactly the kind of access update_quest 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 update_quest:
{
"version": "1",
"default": "deny",
"tools": {
"update_quest": {
"limits": [
{
"counter": "update_quest_rate",
"window": "minute",
"max": 30,
"scope": "grant"
}
]
}
}
}update_quest 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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Update a quest. 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 update_quest: 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.
update_quest 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 update_quest 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 update_quest. 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.
update_quest 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.