This record as markdown: /tools/frontmcp/remove-job.md
What remove_job does on Frontmcp
AI agents call remove_job to permanently remove resources in Frontmcp, typically in cleanup and lifecycle workflows. It does its job in a single call, and there is no undo.
Why remove_job is rated Critical
This tool deletes a job by name, which is an irreversible operation that cannot be undone. While the blast radius is somewhat limited to the job itself (not system-wide), the destructive nature and potential disruption to scheduled/active work justifies 'high' severity.
From the tool's definition 'Remove a dynamic job by name' indicates irreversible deletion of a job resource. The verb 'remove' combined with job lifecycle management constitutes destructive action.
Attacks that exploit this kind of access
The rule that runs remove_job safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Frontmcp, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For remove_job, this is the rule to start with:
remove_job is removed from the agent's tool list entirely, so the agent never calls it. The rest of the server keeps working.
The button opens the PolicyLayer dashboard: create your workspace, connect Frontmcp, apply this rule, and every remove_job call is checked against it from then on.
Questions about remove_job
Remove a dynamic job by name. It is categorised as a Destructive tool in the Frontmcp MCP Server, which means it can permanently delete or destroy data. Block by default and require explicit approval.
Register the Front MCP server in PolicyLayer and add a rule for remove_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 Frontmcp. Nothing to install.
remove_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 remove_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 remove_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.
remove_job is provided by the Front MCP server (agentfront/frontmcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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