remote_disconnect · Jupyter MCP: Risk & Policy

WHAT IT DOES

What remote_disconnect does on JupyterMCP

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

WHY IT NEEDS A POLICY

Why remote_disconnect needs a policy

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

Attacks that exploit this kind of access

Recommended rule Ready

Verdict

remote_disconnect Rate-limited

remote_disconnect 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": {
    "remote_disconnect": {
      "limits": [
        {
          "counter": "remote_disconnect_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 JupyterMCP, so you can run agents against it safely.

FAQ

Questions about remote_disconnect

What does the remote_disconnect tool do? +

Disconnect from the remote Jupyter Server and switch back to local kernels. It is categorised as a Write tool in the JupyterMCP MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

How do I enforce a policy on remote_disconnect? +

Register the Jupyter MCP server in PolicyLayer and add a rule for remote_disconnect: 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 JupyterMCP. Nothing to install.

What risk level is remote_disconnect? +

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

Can I rate-limit remote_disconnect? +

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

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

remote_disconnect is provided by the Jupyter MCP server (try3d/jupytermcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.