This record as markdown: /tools/adamhancock-bullmq-mcp/clean-queue.md
What clean_queue does on BullMQ MCP Server
AI agents call clean_queue to permanently remove resources in BullMQ MCP Server, typically in cleanup and lifecycle workflows. It does its job in a single call, and there is no undo.
Why clean_queue is rated Critical
Cleaning jobs from a queue permanently removes them, which cannot be undone. This matches the Destructive category. Severity is high because an AI agent misusing this tool could wipe out large numbers of jobs across queues, disrupting workloads irreversibly.
From the tool's definition 'Clean jobs from queue' — removing jobs from a queue is an irreversible deletion of pending/completed/failed job records
Attacks that exploit this kind of access
The rule that runs clean_queue safely
PolicyLayer is an MCP gateway: it sits between your AI agents and BullMQ MCP Server, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For clean_queue, this is the rule to start with:
clean_queue 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 BullMQ MCP Server, apply this rule, and every clean_queue call is checked against it from then on.
Questions about clean_queue
Clean jobs from queue. It is categorised as a Destructive tool in the BullMQ MCP Server MCP Server, which means it can permanently delete or destroy data. Block by default and require explicit approval.
Register the BullMQ MCP Server MCP server in PolicyLayer and add a rule for clean_queue: 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 BullMQ MCP Server. Nothing to install.
clean_queue 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 clean_queue 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 clean_queue. 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.
clean_queue is provided by the BullMQ MCP Server MCP server (adamhancock/bullmq-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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