AI agents call list_flows_with_triggers to retrieve information from Kestra Python MCP Server without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool appears to query and retrieve a list of Kestra flows, optionally filtered by trigger status. No description is provided, but the name clearly indicates a listing/read operation. While the description is empty (which lowers confidence slightly from 0.95 to 0.9), the naming convention is unambiguous. Listing flows has no side effects on the system state—it merely retrieves information.
From the tool's definition Tool name contains 'list_flows' which indicates retrieval of flow information without modification. The verb 'list' is typical of Read operations that query/enumerate data.
Documented attack patterns abuse exactly the kind of access list_flows_with_triggers 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 list_flows_with_triggers:
{
"version": "1",
"default": "deny",
"tools": {
"list_flows_with_triggers": {}
}
}list_flows_with_triggers is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.
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list_flows_with_triggers. It is categorised as a Read tool in the Kestra Python MCP Server MCP Server, which means it retrieves data without modifying state.
Register the Kestra Python MCP Server MCP server in PolicyLayer and add a rule for list_flows_with_triggers: 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.
list_flows_with_triggers is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the list_flows_with_triggers 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 list_flows_with_triggers. 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.
list_flows_with_triggers 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.
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39 Kestra Python MCP Server tools catalogued and risk-classified — across an index of 43,000+ MCP servers.