resume_execution

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/resume-execution.md

WHAT IT DOES

What resume_execution does on Kestra Python MCP Server

AI agents invoke resume_execution 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 resume_execution is rated High

The name strongly implies resuming a paused or suspended workflow execution, which triggers external operations in the Kestra workflow engine. Given the server context (flow management, executions), this is an Execute-category action. Confidence is reduced due to the empty description, but 'resume' consistently means triggering continuation of a stopped process.

From the tool's definition Tool name 'resume_execution' on a server that handles Kestra workflow executions; description is empty

Attacks that exploit this kind of access

RECOMMENDED RULE

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

resume_execution Rate-limited

resume_execution 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": {
    "resume_execution": {
      "limits": [
        {
          "counter": "resume_execution_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 resume_execution call is checked against it from then on.

FAQ

Questions about resume_execution

What does the resume_execution tool do? +

resume_execution 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 resume_execution? +

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

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

Can I rate-limit resume_execution? +

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

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

resume_execution 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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