sandbox_kernel_restart

Restart the persistent Jupyter kernel for a

SERVEREasyBits SOURCE@easybits.cloud/mcp

High RISK CLASS

Category Execute

Parameters 00 required

Recommended Rate-limitedsee the rule below

Registry record Grade D, identity unverified Pull the record →

This record as markdown: /tools/cloud-easybits-easybits/sandbox-kernel-restart.md

WHAT IT DOES

What sandbox_kernel_restart does on EasyBits

AI agents invoke sandbox_kernel_restart to trigger actions in EasyBits. 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.

RISK

Why sandbox_kernel_restart is rated High

Restarting a kernel interrupts execution and affects persistent state; root access amplifies blast radius.

From the tool's definition restart Jupyter kernel, persistent microVM, root access

Attacks that exploit this kind of access

RECOMMENDED RULE

The rule that runs sandbox_kernel_restart safely

PolicyLayer is an MCP gateway: it sits between your AI agents and EasyBits, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For sandbox_kernel_restart, this is the rule to start with:

sandbox_kernel_restart Rate-limited

sandbox_kernel_restart 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": {
    "sandbox_kernel_restart": {
      "limits": [
        {
          "counter": "sandbox_kernel_restart_rate",
          "window": "minute",
          "max": 10,
          "scope": "grant"
        }
      ]
    }
  }
}

RATE-LIMIT THIS TOOL → Instant setup, no code required.

The button opens the PolicyLayer dashboard: create your workspace, connect EasyBits, apply this rule, and every sandbox_kernel_restart call is checked against it from then on.

FAQ

Questions about sandbox_kernel_restart

What does the sandbox_kernel_restart tool do? +

Restart the persistent Jupyter kernel for a. It is categorised as a Execute tool in the EasyBits MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.

How do I enforce a policy on sandbox_kernel_restart? +

Register the EasyBits MCP server in PolicyLayer and add a rule for sandbox_kernel_restart: 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 EasyBits. Nothing to install.

What risk level is sandbox_kernel_restart? +

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

Can I rate-limit sandbox_kernel_restart? +

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

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

sandbox_kernel_restart is provided by the EasyBits MCP server (@easybits.cloud/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

KEEP EXPLORING

More on EasyBits, and thousands of servers like it.

This server

All 273 EasyBits tools → High-risk tools on this server →

Across the catalogue

All high-risk MCP tools → The MCP Attack Database →

Guides

Govern code and CI agents →Agent sandbox →Least privilege for MCP →