notebook_execute_all · Jupyter MCP: Risk & Policy

WHAT IT DOES

What notebook_execute_all does on JupyterMCP

AI agents invoke notebook_execute_all to trigger actions in JupyterMCP. 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 notebook_execute_all needs a policy

This tool executes code—specifically all cells in a notebook—whose effects depend on cell contents. While not inherently destructive, notebook execution can modify system state, write files, make network requests, or trigger other side effects determined by notebook code. Execution tools carry high risk if an agent misuses them.

From the tool's definition Tool name is 'notebook_execute_all' and server explicitly describes enabling agents to 'execute Jupyter notebook cells'. The empty description is consistent with a tool that executes all cells in a notebook.

Risk signalsBulk/mass operation — affects multiple targets

Attacks that exploit this kind of access

Recommended rule Ready

Verdict

notebook_execute_all Rate-limited

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

FAQ

Questions about notebook_execute_all

What does the notebook_execute_all tool do? +

notebook_execute_all. It is categorised as a Execute tool in the JupyterMCP MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.

How do I enforce a policy on notebook_execute_all? +

Register the Jupyter MCP server in PolicyLayer and add a rule for notebook_execute_all: 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 notebook_execute_all? +

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

Can I rate-limit notebook_execute_all? +

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

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

notebook_execute_all 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.