kaggle_run_notebook · Mcp Kaggle Tool MCP: Risk & Policy

WHAT IT DOES

What kaggle_run_notebook does on Mcp Kaggle Tool

AI agents invoke kaggle_run_notebook to trigger actions in Mcp Kaggle Tool. What it does depends on the arguments the agent supplies, and its effects often reach beyond the immediate call — builds kicked off, notifications sent, workflows started.

WHY IT NEEDS A POLICY

Why kaggle_run_notebook needs a policy

This tool triggers execution of code (a Kaggle notebook) whose effects depend entirely on the notebook's contents and arguments. While not inherently destructive, notebook execution can modify data, make API calls, or perform compute-intensive operations. The high severity reflects the broad potential impact of arbitrary code execution in a data science context.

From the tool's definition Tool name contains 'run/execute' and description states 'Run/execute a Kaggle notebook'. Notebooks are executable code artifacts that can perform arbitrary operations including data processing, API calls, and external integrations.

Attacks that exploit this kind of access

Recommended rule Ready

Verdict

kaggle_run_notebook Rate-limited

kaggle_run_notebook stays usable, but rate-capped — a runaway agent can't fire it dozens of times a minute. Everything else on the server is denied unless you say otherwise.

View as policy code

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "kaggle_run_notebook": {
      "limits": [
        {
          "counter": "kaggle_run_notebook_rate",
          "window": "minute",
          "max": 10,
          "scope": "grant"
        }
      ]
    }
  }
}

RATE-LIMIT THIS TOOL →

Instant setup, no code required.

PolicyLayer is an MCP gateway: every tool call is checked against your rule before it reaches Mcp Kaggle Tool, so you can run agents against it safely.

FAQ

Questions about kaggle_run_notebook

What does the kaggle_run_notebook tool do? +

Run/execute a Kaggle notebook. It is categorised as a Execute tool in the Mcp Kaggle Tool MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.

How do I enforce a policy on kaggle_run_notebook? +

Register the Mcp Kaggle Tool MCP server in PolicyLayer and add a rule for kaggle_run_notebook: 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 Mcp Kaggle Tool. Nothing to install.

What risk level is kaggle_run_notebook? +

kaggle_run_notebook is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.

Can I rate-limit kaggle_run_notebook? +

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

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

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