jupyter_connect_notebook · XL MCP: Risk & Policy

WHAT IT DOES

What jupyter_connect_notebook does on XLMCP

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

WHY IT NEEDS A POLICY

Why jupyter_connect_notebook needs a policy

An AI agent can call jupyter_connect_notebook faster than any human can review — one bad instruction and it creates or modifies resources in XLMCP by the hundred, each call as confident as the last.

Attacks that exploit this kind of access

Recommended rule Ready

Verdict

jupyter_connect_notebook Rate-limited

jupyter_connect_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_connect_notebook": {
      "limits": [
        {
          "counter": "jupyter_connect_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 XLMCP, so you can run agents against it safely.

FAQ

Questions about jupyter_connect_notebook

What does the jupyter_connect_notebook tool do? +

jupyter_connect_notebook. It is categorised as a Write tool in the XLMCP 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_connect_notebook? +

Register the XL MCP server in PolicyLayer and add a rule for jupyter_connect_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 XLMCP. Nothing to install.

What risk level is jupyter_connect_notebook? +

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

Can I rate-limit jupyter_connect_notebook? +

Yes. Add a rate_limit block to the jupyter_connect_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_connect_notebook completely? +

Set action: deny in the PolicyLayer policy for jupyter_connect_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_connect_notebook? +

jupyter_connect_notebook is provided by the XL MCP server (xlydiansoftware/aix). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.