model_delete

Delete a model.

SERVERKaggle-MCP SOURCE54yyyu/kaggle-mcp

Critical RISK CLASS

Category Destructive

Parameters 00 required

Recommended Hiddensee the rule below

Registry record Grade F, identity unverified Pull the record →

This record as markdown: /tools/54yyyu-kaggle-mcp/model-delete.md

WHAT IT DOES

What model_delete does on Kaggle-MCP

AI agents call model_delete to permanently remove resources in Kaggle-MCP, typically in cleanup and lifecycle workflows. It does its job in a single call, and there is no undo.

RISK

Why model_delete is rated Critical

The tool performs an irreversible deletion operation on a Kaggle model resource. Once deleted, the model cannot be recovered without external backup. This is a destructive action with high blast radius if invoked unintentionally by an AI agent (e.g., deleting a user's competition or portfolio model). While not financial in nature, it represents loss of user-created assets and intellectual property.

From the tool's definition Tool name is 'model_delete' with description 'Delete a model.' The verb 'Delete' directly indicates irreversible removal of data.

Attacks that exploit this kind of access

RECOMMENDED RULE

The rule that runs model_delete safely

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

model_delete Hidden

model_delete is removed from the agent's tool list entirely, so the agent never calls it. The rest of the server keeps working.

View as policy code

policy.json

{
  "version": "1",
  "default": "deny",
  "hide": [
    "model_delete"
  ]
}

RESTRICT THIS TOOL → Instant setup, no code required.

The button opens the PolicyLayer dashboard: create your workspace, connect Kaggle-MCP, apply this rule, and every model_delete call is checked against it from then on.

FAQ

Questions about model_delete

What does the model_delete tool do? +

Delete a model. It is categorised as a Destructive tool in the Kaggle-MCP MCP Server, which means it can permanently delete or destroy data. Block by default and require explicit approval.

How do I enforce a policy on model_delete? +

Register the Kaggle MCP server in PolicyLayer and add a rule for model_delete: 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 Kaggle-MCP. Nothing to install.

What risk level is model_delete? +

model_delete is a Destructive tool with critical risk. Critical-risk tools should be blocked by default and only enabled with explicit human approval.

Can I rate-limit model_delete? +

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

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

model_delete is provided by the Kaggle MCP server (54yyyu/kaggle-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

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