jupyter_save_notebook · ML Jupyter MCP: Risk & Policy

WHAT IT DOES

What jupyter_save_notebook does on ML Jupyter MCP

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

WHY IT NEEDS A POLICY

Why jupyter_save_notebook needs a policy

This tool creates or modifies notebook files, which is a Write operation. While reversible, it persists code execution state to storage, potentially capturing sensitive computational results, variable values, or imported credentials.

From the tool's definition Tool name 'jupyter_save_notebook' and description 'Save the current session state to a notebook' indicate creation/modification of notebook files on disk. The action is reversible (files can be overwritten or deleted).

Attacks that exploit this kind of access

Recommended rule Ready

Verdict

jupyter_save_notebook Rate-limited

jupyter_save_notebook 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": {
    "jupyter_save_notebook": {
      "limits": [
        {
          "counter": "jupyter_save_notebook_rate",
          "window": "minute",
          "max": 30,
          "scope": "grant"
        }
      ]
    }
  }
}

LIMIT THIS TOOL →

Instant setup, no code required.

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

FAQ

Questions about jupyter_save_notebook

What does the jupyter_save_notebook tool do? +

Save the current session state to a notebook. It is categorised as a Write tool in the ML Jupyter 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 jupyter_save_notebook? +

Register the ML Jupyter MCP server in PolicyLayer and add a rule for jupyter_save_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 ML Jupyter MCP. Nothing to install.

What risk level is jupyter_save_notebook? +

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

Can I rate-limit jupyter_save_notebook? +

Yes. Add a rate_limit block to the jupyter_save_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 jupyter_save_notebook completely? +

Set action: deny in the PolicyLayer policy for jupyter_save_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 jupyter_save_notebook? +

jupyter_save_notebook is provided by the ML Jupyter MCP server (mayank-ketkar-sf/claudejupy). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.