AI agents call delete_flow_logs to permanently remove resources in Kestra Python MCP Server — typically in cleanup and lifecycle workflows. It does its job in a single call, and there is no undo.
The 'delete' operation in the tool name indicates this is a destructive action that irreversibly removes log data. Although the description is empty (lowering confidence slightly), the explicit 'delete' verb in a logging/workflow management context clearly indicates data destruction.
From the tool's definition Tool name 'delete_flow_logs' explicitly contains 'delete', indicating irreversible removal of data. The sibling context shows this server manages Kestra workflows and their execution logs. Deletion of logs cannot be undone.
Documented attack patterns abuse exactly the kind of access delete_flow_logs gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Kestra Python MCP Server, and nothing reaches the server without passing your rules. This is the rule we recommend for delete_flow_logs:
{
"version": "1",
"default": "deny",
"hide": [
"delete_flow_logs"
]
}delete_flow_logs disappears from the agent's tool list entirely, and any attempt to call it is denied. The rest of the server keeps working.
Free to start. No card required.
delete_flow_logs. It is categorised as a Destructive tool in the Kestra Python MCP Server MCP Server, which means it can permanently delete or destroy data. Block by default and require explicit approval.
Register the Kestra Python MCP Server MCP server in PolicyLayer and add a rule for delete_flow_logs: 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.
delete_flow_logs is a Destructive tool with critical risk. Critical-risk tools should be blocked by default and only enabled with explicit human approval.
Yes. Add a rate_limit block to the delete_flow_logs 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.
Set action: deny in the PolicyLayer policy for delete_flow_logs. 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.
delete_flow_logs 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.
Start from Kestra Python MCP Server, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
Free to start. No card required.
39 Kestra Python MCP Server tools catalogued and risk-classified — across an index of 43,000+ MCP servers.