Cancel a dataset build or purge a completed dataset.
AI agents call cancel_dataset to permanently remove resources in Macrocosmos MCP — typically in cleanup and lifecycle workflows. It does its job in a single call, and there is no undo.
The 'purge' function explicitly removes data that cannot be recovered, placing this in the Destructive category. While 'cancel' operations are typically Write-level, the purge capability makes this irreversible. Severity is high because purging a dataset could lose significant collected data from X/Twitter and Reddit queries, impacting data availability and research workflows.
From the tool's definition Tool description states it can 'purge a completed dataset', which is irreversible data deletion. It also cancels in-progress dataset builds, which destroys accumulated work/state.
Documented attack patterns abuse exactly the kind of access cancel_dataset gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Macrocosmos MCP, and nothing reaches the server without passing your rules. This is the rule we recommend for cancel_dataset:
{
"version": "1",
"default": "deny",
"hide": [
"cancel_dataset"
]
}cancel_dataset disappears from the agent's tool list entirely, and any attempt to call it is denied. The rest of the server keeps working.
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Cancel a dataset build or purge a completed dataset. It is categorised as a Destructive tool in the Macrocosmos MCP MCP Server, which means it can permanently delete or destroy data. Block by default and require explicit approval.
Register the Macrocosmos MCP server in PolicyLayer and add a rule for cancel_dataset: 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 Macrocosmos MCP. Nothing to install.
cancel_dataset is a Destructive tool with critical risk. Critical-risk tools should be blocked by default and only enabled with explicit human approval.
Yes. Add a rate_limit block to the cancel_dataset 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 cancel_dataset. 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.
cancel_dataset is provided by the Macrocosmos MCP server (macrocosm-os/macrocosmos-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Macrocosmos MCP, 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.
6 Macrocosmos MCP tools catalogued and risk-classified — across an index of 43,000+ MCP servers.