model_instance_update

A write tool on the Kaggle- MCP server.

SERVERKaggle-MCP SOURCE54yyyu/kaggle-mcp

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/54yyyu-kaggle-mcp/model-instance-update.md

WHAT IT DOES

What model_instance_update does on Kaggle-MCP

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

RISK

Why model_instance_update is rated Medium

The 'update' verb in the tool name suggests reversible modification of data (a model instance), placing it in the Write category. Given the Kaggle context (competitions, datasets, kernels), this likely modifies user-owned model configuration or state. Severity is medium because unintended modifications could corrupt a user's model setup, but the blast radius is limited to that user's model instance.

From the tool's definition Tool name 'model_instance_update' indicates modification of a model instance. No description provided, requiring inference from name alone.

Attacks that exploit this kind of access

RECOMMENDED RULE

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

model_instance_update Rate-limited

model_instance_update 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": {
    "model_instance_update": {
      "limits": [
        {
          "counter": "model_instance_update_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 Kaggle-MCP, apply this rule, and every model_instance_update call is checked against it from then on.

FAQ

Questions about model_instance_update

What does the model_instance_update tool do? +

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

How do I enforce a policy on model_instance_update? +

Register the Kaggle MCP server in PolicyLayer and add a rule for model_instance_update: 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_instance_update? +

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

Can I rate-limit model_instance_update? +

Yes. Add a rate_limit block to the model_instance_update 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_instance_update completely? +

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

model_instance_update 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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