jupyter_interrupt_kernel · Multi-Tool MCP Server MCP

WHAT IT DOES

What jupyter_interrupt_kernel does on Multi-Tool MCP Server

AI agents invoke jupyter_interrupt_kernel to trigger actions in Multi-Tool MCP Server. 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 jupyter_interrupt_kernel needs a policy

This tool stops the current execution of a Jupyter kernel, which is an active intervention in a running compute process. It is an Execute-category action as it triggers an external operation (kernel interruption) that affects ongoing code execution. While it doesn't delete data, it can disrupt running computations, potentially causing data loss or incomplete operations.

From the tool's definition Interrupt a running Jupyter kernel (stop current execution)

Attacks that exploit this kind of access

Recommended rule Ready

Verdict

jupyter_interrupt_kernel Rate-limited

jupyter_interrupt_kernel 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": {
    "jupyter_interrupt_kernel": {
      "limits": [
        {
          "counter": "jupyter_interrupt_kernel_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 Multi-Tool MCP Server, so you can run agents against it safely.

FAQ

Questions about jupyter_interrupt_kernel

What does the jupyter_interrupt_kernel tool do? +

Interrupt a running Jupyter kernel (stop current execution). It is categorised as a Execute tool in the Multi-Tool MCP Server MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.

How do I enforce a policy on jupyter_interrupt_kernel? +

Register the Multi-Tool MCP Server MCP server in PolicyLayer and add a rule for jupyter_interrupt_kernel: 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 Multi-Tool MCP Server. Nothing to install.

What risk level is jupyter_interrupt_kernel? +

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

Can I rate-limit jupyter_interrupt_kernel? +

Yes. Add a rate_limit block to the jupyter_interrupt_kernel 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_interrupt_kernel completely? +

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

jupyter_interrupt_kernel is provided by the Multi-Tool MCP Server MCP server (shawn-falconbury/mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.