search_flows

A read tool on the Kestra Python MCP server.

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

Low RISK CLASS

Category Read

Parameters 00 required

Recommended Allowedsee the rule below

Registry record Grade F, identity unverified Pull the record →

This record as markdown: /tools/kestra-io-mcp-server-python/search-flows.md

WHAT IT DOES

What search_flows does on Kestra Python MCP Server

AI agents call search_flows 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.

RISK

Why search_flows is rated Low

Search operations retrieve data without side effects. The naming convention aligns with typical read operations. Absence of description lowers confidence slightly, but the tool name itself is clear enough to classify as a Read operation with low blast radius if misused by an AI agent.

From the tool's definition Tool name 'search_flows' indicates a search/query operation. While the description is empty, the name and context of sibling tools (which include destructive operations like delete_execution_logs and delete_flow_logs) suggest this is a read-only query…

Attacks that exploit this kind of access

RECOMMENDED RULE

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

search_flows Allowed

search_flows is read-only, so it stays allowed. Everything else on the server is denied unless you say otherwise.

View as policy code

policy.json

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

ALLOW ONLY 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 search_flows call is checked against it from then on.

FAQ

Questions about search_flows

What does the search_flows tool do? +

search_flows is a read tool on the Kestra Python MCP Server MCP server. It is categorised as a Read tool in the Kestra Python MCP Server MCP Server, which means it retrieves data without modifying state.

How do I enforce a policy on search_flows? +

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

search_flows is a Read tool with low risk. Read-only tools are generally safe to allow by default.

Can I rate-limit search_flows? +

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

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

search_flows 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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