change_taskrun_state

A execute tool on the Kestra Python MCP server.

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

High RISK CLASS

Category Execute

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/change-taskrun-state.md

WHAT IT DOES

What change_taskrun_state does on Kestra Python MCP Server

AI agents invoke change_taskrun_state 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.

RISK

Why change_taskrun_state is rated High

Changing the state of a task run in a workflow orchestration system like Kestra is an execution-level operation — it affects the runtime behavior of workflows. This could resume, pause, fail, or otherwise alter in-flight executions. The sibling tools (execute_flow, force_run_execution, backfill_executions) confirm this server manages workflow execution states.

From the tool's definition Tool name 'change_taskrun_state' suggests modifying the execution state of a task run, which is an operational action affecting workflow execution. Description is empty, lowering confidence.

Attacks that exploit this kind of access

RECOMMENDED RULE

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

change_taskrun_state Rate-limited

change_taskrun_state 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.

View as policy code

policy.json

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

RATE-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 change_taskrun_state call is checked against it from then on.

FAQ

Questions about change_taskrun_state

What does the change_taskrun_state tool do? +

change_taskrun_state is a execute tool on the Kestra Python MCP Server MCP server. It is categorised as a Execute tool in the Kestra Python MCP Server MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.

How do I enforce a policy on change_taskrun_state? +

Register the Kestra Python MCP Server MCP server in PolicyLayer and add a rule for change_taskrun_state: 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 change_taskrun_state? +

change_taskrun_state is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.

Can I rate-limit change_taskrun_state? +

Yes. Add a rate_limit block to the change_taskrun_state 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 change_taskrun_state completely? +

Set action: deny in the PolicyLayer policy for change_taskrun_state. 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 change_taskrun_state? +

change_taskrun_state 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.

KEEP EXPLORING

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