execute_flow

What execute_flow does on Kestra Python MCP Server

AI agents invoke execute_flow to trigger actions in Kestra Python 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 execute_flow is rated High

This tool triggers the execution of a Kestra workflow, which runs external operations whose effects depend on the workflow definition and arguments. This is a classic Execute category action—it initiates computation/operations that may have side effects. Severity is high because executing arbitrary workflows could consume resources, trigger external integrations, or perform unintended business logic.

From the tool's definition Tool name is 'execute_flow' and the server description indicates it 'enables AI assistants to interact with Kestra workflows through natural language, supporting operations like flow management, executions, backfills, and other Kestra features.' The tool…

The rule that runs execute_flow safely

PolicyLayer is an MCP gateway: it sits between your AI agents and Kestra Python MCP Server, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For execute_flow, this is the rule to start with:

{
  "version": "1",
  "default": "deny",
  "tools": {
    "execute_flow": {
      "limits": [
        {
          "counter": "execute_flow_rate",
          "window": "minute",
          "max": 10,
          "scope": "grant"
        }
      ]
    }
  }
}

Questions about execute_flow