This record as markdown: /tools/adamhancock-bullmq-mcp/resume-queue.md
What resume_queue does on BullMQ MCP Server
AI agents invoke resume_queue to trigger actions in BullMQ MCP Server. What it does depends on the arguments the agent supplies, and its effects often reach beyond the immediate call: builds kicked off, notifications sent, workflows started.
Why resume_queue is rated High
Resuming a queue triggers external operations by restarting job processing in BullMQ/Redis. This is an operational state change that causes workers to begin executing jobs again, making it an Execute-category action. It is reversible (can be paused again), so it doesn't qualify as Destructive. Misuse could cause unintended job execution at scale, hence medium severity.
From the tool's definition Resume queue processing
Attacks that exploit this kind of access
The rule that runs resume_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 resume_queue, this is the rule to start with:
resume_queue stays usable, but rate-capped: a runaway agent can't fire it dozens of times a minute. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect BullMQ MCP Server, apply this rule, and every resume_queue call is checked against it from then on.
Questions about resume_queue
Resume queue processing. It is categorised as a Execute tool in the BullMQ MCP Server MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the BullMQ MCP Server MCP server in PolicyLayer and add a rule for resume_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.
resume_queue is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.
Yes. Add a rate_limit block to the resume_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 resume_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.
resume_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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