list_executions

What list_executions does on Kestra Python MCP Server

AI agents call list_executions to retrieve information from Kestra Python MCP Server without modifying anything. It is typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.

Why list_executions is rated Low

The tool retrieves or queries execution records from Kestra without modifying, executing, or deleting data. Even with an empty description, the imperative 'list' strongly indicates a read operation that returns a collection of existing executions. No side effects are implied. Severity is low because listing data poses minimal risk—worst case is information disclosure of workflow execution metadata.

From the tool's definition Tool name 'list_executions' indicates retrieval of execution data; description is empty but naming convention is clear. Sibling context shows this server manages workflow operations, and 'list_*' patterns universally denote read-only queries.

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

{
  "version": "1",
  "default": "deny",
  "tools": {
    "list_executions": {}
  }
}

Questions about list_executions