cursor_resume_task

THE RISK

Low Risk

Why cursor_resume_task needs a policy

The tool retrieves a resume command string and refreshes status information — it reads/queries existing task state rather than creating, modifying, or executing anything directly. The 'refresh' aspect is a minor state update but the primary purpose is informational retrieval.

From the tool's definition 'Return the Cursor resume command for a delegated task and refresh its last known status'

Documented attack patterns abuse exactly the kind of access cursor_resume_task gives an agent:

POLICY

How to control cursor_resume_task

PolicyLayer is an MCP gateway — it sits between your AI agents and Agent Orchestration, and nothing reaches the server without passing your rules. This is the rule we recommend for cursor_resume_task:

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "cursor_resume_task": {}
  }
}

cursor_resume_task is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.

Create a free account and register Agent Orchestration — nothing to install.
Add this policy — paste it, or build it visually.
Point your MCP client (Claude, Cursor, anything) at your gateway URL.

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EXPLORE

Related tools and policies

More Agent Orchestration tools

Destructive memory_delete Delete a value from shared memory. Destructive agent_unregister Unregister this agent and release all held locks. Call at the end of your session. Execute bootstrap Initialize agent session: register (if needed), get current focus, pending tasks, and rece Execute cursor_recover_task Recover a failed or stale delegated Cursor task by relaunching it with the latest shared c Execute lock_acquire Acquire a lock on a resource to prevent concurrent access. Write claim_todo FOR SUB-AGENTS: Register yourself AND claim a specific task in one call. Use this when you Write cursor_delegate_task Delegate a task to Cursor CLI and store session metadata for later resume/sync. Write cursor_sync_task Refresh a delegated Cursor task, sync the latest provider status, and persist knowledge ba

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Go deeper

The MCP Attack Database → Documented attack patterns against MCP deployments — and the policies that stop them.
Data exfiltration → How read access becomes an exfiltration channel when chained with untrusted content.
MCP token cost → What connecting this server costs in context-window tokens on every request.
Rate Limiting MCP Tool Calls: A Practical Guide →
MCP Security: Why Prompt Guardrails Aren't Enough →

FAQ

Questions about cursor_resume_task

What does the cursor_resume_task tool do? +

Return the Cursor resume command for a delegated task and refresh its last known status. It is categorised as a Read tool in the Agent Orchestration MCP Server, which means it retrieves data without modifying state.

How do I enforce a policy on cursor_resume_task? +

Register the Agent Orchestration MCP server in PolicyLayer and add a rule for cursor_resume_task: 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 Agent Orchestration. Nothing to install.

What risk level is cursor_resume_task? +

cursor_resume_task is a Read tool with low risk. Read-only tools are generally safe to allow by default.

Can I rate-limit cursor_resume_task? +

Yes. Add a rate_limit block to the cursor_resume_task 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.

How do I block cursor_resume_task completely? +

Set action: deny in the PolicyLayer policy for cursor_resume_task. 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.

What MCP server provides cursor_resume_task? +

cursor_resume_task is provided by the Agent Orchestration MCP server (madebyaris/agent-orchestration). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every Agent Orchestration tool call.

Start from Agent Orchestration, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.

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