manage_flow

A write tool on the Kestra Python MCP server.

SERVERKestra Python MCP Server SOURCEkestra-io/mcp-server-python

Medium RISK CLASS

Category Write

Parameters 00 required

Recommended Rate-limitedsee the rule below

Registry record Grade F, identity unverified Pull the record →

This record as markdown: /tools/kestra-io-mcp-server-python/manage-flow.md

WHAT IT DOES

What manage_flow does on Kestra Python MCP Server

AI agents use manage_flow to create or update resources in Kestra Python MCP Server, usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Kestra Python MCP Server environment.

RISK

Why manage_flow is rated Medium

The name 'manage_flow' suggests creating, updating, or modifying Kestra flows. Given the server context (flow management, executions), this likely involves write operations. However, since the description is empty, there is uncertainty — it could also encompass destructive operations like deleting flows. Defaulting to Write as the most probable category, but confidence is low due to missing description.

From the tool's definition Tool name 'manage_flow' on a Kestra workflow server; description is empty and uninformative.

Attacks that exploit this kind of access

RECOMMENDED RULE

The rule that runs manage_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 manage_flow, this is the rule to start with:

manage_flow Rate-limited

manage_flow stays usable, but capped: an agent stuck in a loop can't make hundreds of changes a minute. Everything else on the server is denied unless you say otherwise.

View as policy code

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "manage_flow": {
      "limits": [
        {
          "counter": "manage_flow_rate",
          "window": "minute",
          "max": 30,
          "scope": "grant"
        }
      ]
    }
  }
}

LIMIT THIS TOOL → Instant setup, no code required.

The button opens the PolicyLayer dashboard: create your workspace, connect Kestra Python MCP Server, apply this rule, and every manage_flow call is checked against it from then on.

FAQ

Questions about manage_flow

What does the manage_flow tool do? +

manage_flow is a write tool on the Kestra Python MCP Server MCP server. It is categorised as a Write tool in the Kestra Python MCP Server MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

How do I enforce a policy on manage_flow? +

Register the Kestra Python MCP Server MCP server in PolicyLayer and add a rule for manage_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 Kestra Python MCP Server. Nothing to install.

What risk level is manage_flow? +

manage_flow is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.

Can I rate-limit manage_flow? +

Yes. Add a rate_limit block to the manage_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.

How do I block manage_flow completely? +

Set action: deny in the PolicyLayer policy for manage_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.

What MCP server provides manage_flow? +

manage_flow is provided by the Kestra Python MCP Server MCP server (kestra-io/mcp-server-python). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

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