cancel_dispatch
Cancel a pending or scheduled dispatch. Cannot cancel dispatches that have already been sent.
This record as markdown: /tools/todos/cancel-dispatch.md
What cancel_dispatch does on Todos
AI agents call cancel_dispatch to permanently remove resources in Todos, typically in cleanup and lifecycle workflows. It does its job in a single call, and there is no undo.
Why cancel_dispatch is rated Critical
Cancelling a dispatch is an irreversible action — once cancelled, the scheduled dispatch is removed and cannot be restored. The description explicitly states it cannot cancel already-sent dispatches, implying the cancellation itself is final and permanent for pending/scheduled ones.
From the tool's definition Cancel a pending or scheduled dispatch. Cannot cancel dispatches that have already been sent.
Attacks that exploit this kind of access
The rule that runs cancel_dispatch safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Todos, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For cancel_dispatch, this is the rule to start with:
cancel_dispatch 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 Todos, apply this rule, and every cancel_dispatch call is checked against it from then on.
Questions about cancel_dispatch
Cancel a pending or scheduled dispatch. Cannot cancel dispatches that have already been sent. It is categorised as a Destructive tool in the Todos MCP Server, which means it can permanently delete or destroy data. Block by default and require explicit approval.
Register the Todos MCP server in PolicyLayer and add a rule for cancel_dispatch: 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 Todos. Nothing to install.
cancel_dispatch 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_dispatch 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_dispatch. 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_dispatch is provided by the Todos MCP server (@hasna/todos). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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