update_input_preset

Update an existing input preset. You can only update presets you created.

SERVERFlowDot MCP Server SOURCEflowdot-llc/mcp-server

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/flowdot-llc-mcp-server/update-input-preset.md

WHAT IT DOES

What update_input_preset does on FlowDot MCP Server

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

RISK

Why update_input_preset is rated Medium

The tool modifies existing data (input presets) in a reversible manner, fitting the Write category. Severity is medium because changes to presets could affect workflow execution and downstream processes, but the impact is scoped to the user's own presets (as indicated by the ownership restriction "presets you created"). This is not Destructive (irreversible deletion), Execute (arbitrary code execution), or Financial.

From the tool's definition Tool performs an 'update' operation on input presets, which modifies data reversibly. The description explicitly states "Update an existing input preset," indicating data modification rather than creation or deletion.

Attacks that exploit this kind of access

RECOMMENDED RULE

The rule that runs update_input_preset safely

PolicyLayer is an MCP gateway: it sits between your AI agents and FlowDot MCP Server, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For update_input_preset, this is the rule to start with:

update_input_preset Rate-limited

update_input_preset 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": {
    "update_input_preset": {
      "limits": [
        {
          "counter": "update_input_preset_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 FlowDot MCP Server, apply this rule, and every update_input_preset call is checked against it from then on.

FAQ

Questions about update_input_preset

What does the update_input_preset tool do? +

Update an existing input preset. You can only update presets you created. It is categorised as a Write tool in the FlowDot 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 update_input_preset? +

Register the FlowDot MCP Server MCP server in PolicyLayer and add a rule for update_input_preset: 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 FlowDot MCP Server. Nothing to install.

What risk level is update_input_preset? +

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

Can I rate-limit update_input_preset? +

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

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

update_input_preset is provided by the FlowDot MCP Server MCP server (flowdot-llc/mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

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