manage_kv_store

A write tool on the Kestra Python MCP server.

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

Medium RISK CLASS

Category Write

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/manage-kv-store.md

WHAT IT DOES

What manage_kv_store does on Kestra Python MCP Server

AI agents use manage_kv_store to create or update resources in Kestra Python MCP Server, usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Kestra Python MCP Server environment.

RISK

Why manage_kv_store is rated Medium

The tool name 'manage_kv_store' most naturally implies write operations (create, update, set) on a key-value store without explicit mention of deletion. However, 'manage' is ambiguous and could encompass destructive operations. Without a description, confidence is reduced significantly.

From the tool's definition Tool name 'manage_kv_store' suggests key-value store operations; sibling tools include destructive operations (delete_execution_logs, delete_flow_logs) and write operations (create_flow_from_yaml, execute_flow), but no description provided to clarify exact…

Attacks that exploit this kind of access

RECOMMENDED RULE

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

manage_kv_store Rate-limited

manage_kv_store stays usable, but capped: an agent stuck in a loop can't make hundreds of changes a minute. Everything else on the server is denied unless you say otherwise.

View as policy code

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "manage_kv_store": {
      "limits": [
        {
          "counter": "manage_kv_store_rate",
          "window": "minute",
          "max": 30,
          "scope": "grant"
        }
      ]
    }
  }
}

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 manage_kv_store call is checked against it from then on.

FAQ

Questions about manage_kv_store

What does the manage_kv_store tool do? +

manage_kv_store is a write tool on the Kestra Python MCP Server MCP server. It is categorised as a Write tool in the Kestra Python MCP Server MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

How do I enforce a policy on manage_kv_store? +

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

manage_kv_store is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.

Can I rate-limit manage_kv_store? +

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

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

manage_kv_store 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.

KEEP EXPLORING

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