stop_cloudflow_flow
Manage CloudFlow. Stops the run currently in progress for the given flow. The run is identified from the flow alone — no run ID is needed, since a flow can only have one run active at a time. No Idempotency-Key is required. This is a state transition, not a resource creation. Returns 409 when the...
This record as markdown: /tools/doit/stop-cloudflow-flow.md
What stop_cloudflow_flow does on Doit
AI agents invoke stop_cloudflow_flow to trigger actions in Doit. 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.
| Parameter | Type | Required | Description |
|---|---|---|---|
flowId | string | Yes | |
customerContext | string | — | Scope the request to a specific customer by ID. Required for DoiT employees (whose token isn't tied to a single customer); omit for direct customer users. |
Parameters from the server's own tool schema.
Why stop_cloudflow_flow is rated High
stop_cloudflow_flow triggers real processes with real consequences. An agent gone sideways doesn't fire it once. It starts dozens of builds, sends mass notifications, or burns through compute before anyone looks up.
Attacks that exploit this kind of access
The rule that runs stop_cloudflow_flow safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Doit, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For stop_cloudflow_flow, this is the rule to start with:
stop_cloudflow_flow 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 Doit, apply this rule, and every stop_cloudflow_flow call is checked against it from then on.
Questions about stop_cloudflow_flow
Manage CloudFlow. Stops the run currently in progress for the given flow. The run is identified from the flow alone — no run ID is needed, since a flow can only have one run active at a time. No Idempotency-Key is required. This is a state transition, not a resource creation. Returns 409 when the flow has no run in progress, which includes a run that reached a terminal state between this request and the stop attempt. It is categorised as a Execute tool in the Doit MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
stop_cloudflow_flow accepts 2 parameters: flowId, customerContext. Required: flowId. The full parameter table on this page comes from the server's own tool schema.
Register the Doit MCP server in PolicyLayer and add a rule for stop_cloudflow_flow: 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 Doit. Nothing to install.
stop_cloudflow_flow 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 stop_cloudflow_flow 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 stop_cloudflow_flow. 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.
stop_cloudflow_flow is provided by the Doit MCP server (@doitintl/doit-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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