trigger_cloudflow_flow
Manage CloudFlow. Starts a run of a published flow whose first node is a webhook, scheduled, or manual trigger. A draft flow is rejected with 422 — use actions/test-run to run one. No Idempotency-Key is required. This is a state transition, not a resource creation. The response is a snapshot take...
This record as markdown: /tools/doit/trigger-cloudflow-flow.md
What trigger_cloudflow_flow does on Doit
AI agents invoke trigger_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 trigger_cloudflow_flow is rated High
trigger_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 trigger_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 trigger_cloudflow_flow, this is the rule to start with:
trigger_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 trigger_cloudflow_flow call is checked against it from then on.
Questions about trigger_cloudflow_flow
Manage CloudFlow. Starts a run of a published flow whose first node is a webhook, scheduled, or manual trigger. A draft flow is rejected with 422 — use actions/test-run to run one. No Idempotency-Key is required. This is a state transition, not a resource creation. The response is a snapshot taken at dispatch, so status is always pending and the timing fields are not yet populated. Read the run back through GET /cloudflow/v1/flows/{flowId}/runs/{runId} to follow its progress. A flow holds a concurrency lock while it runs, so triggering one that is already running returns 409 with the active run embedded in the problem body — no second lookup needed. The current generated MCP schema exposes no arbitrary trigger payload field; the API uses an empty payload when omitted. trigger_cloud_flow accepts a webhook payload for published webhook flows. 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.
trigger_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 trigger_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.
trigger_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 trigger_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 trigger_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.
trigger_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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