Cancel a Serverless job that is queued or in progress.
AI agents call cancel-job to permanently remove resources in RunPod MCP Server — typically in cleanup and lifecycle workflows. It does its job in a single call, and there is no undo.
Cancelling a job is an irreversible action — a running or queued job that is cancelled cannot be restarted from the same state; the work done is lost. This goes beyond a simple write/modify and constitutes an irreversible termination of an in-progress operation, placing it in the Destructive category.
From the tool's definition Cancel a Serverless job that is queued or in progress
Documented attack patterns abuse exactly the kind of access cancel-job gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and RunPod MCP Server, and nothing reaches the server without passing your rules. This is the rule we recommend for cancel-job:
{
"version": "1",
"default": "deny",
"hide": [
"cancel-job"
]
}cancel-job 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 Serverless job that is queued or in progress. It is categorised as a Destructive tool in the RunPod MCP Server MCP Server, which means it can permanently delete or destroy data. Block by default and require explicit approval.
Register the RunPod MCP Server MCP server in PolicyLayer and add a rule for cancel-job: 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 RunPod MCP Server. Nothing to install.
cancel-job 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-job 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-job. 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-job is provided by the RunPod MCP Server MCP server (runpod/runpod-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic rules across all 36 RunPod MCP Server tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
Free to start. No card required.
36 RunPod MCP Server tools catalogued and risk-classified — across an index of 42,500+ MCP servers.