ipynb_replace_cells_batch · Jupyter Editor MCP

WHAT IT DOES

What ipynb_replace_cells_batch does on Jupyter Editor

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

WHY IT NEEDS A POLICY

Why ipynb_replace_cells_batch needs a policy

Batch replacement of notebook cells modifies data (cell content) in a reversible manner—changes can be undone by replacing again with original content. This is a Write operation rather than Execute because the tool itself doesn't run code; it edits notebook structure/content. Severity is high because batch operations on notebooks could affect multiple cells/analyses at scale, though damage is recoverable.

From the tool's definition Tool name 'ipynb_replace_cells_batch' indicates batch replacement of notebook cells. Sibling tools include ipynb_append_cell, ipynb_delete_cell, and ipynb_clear_outputs, establishing this server's pattern of modifying notebook content.

Attacks that exploit this kind of access

Recommended rule Ready

Verdict

ipynb_replace_cells_batch Rate-limited

ipynb_replace_cells_batch 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": {
    "ipynb_replace_cells_batch": {
      "limits": [
        {
          "counter": "ipynb_replace_cells_batch_rate",
          "window": "minute",
          "max": 30,
          "scope": "grant"
        }
      ]
    }
  }
}

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PolicyLayer is an MCP gateway: every tool call is checked against your rule before it reaches Jupyter Editor, so you can run agents against it safely.

FAQ

Questions about ipynb_replace_cells_batch

What does the ipynb_replace_cells_batch tool do? +

ipynb_replace_cells_batch. It is categorised as a Write tool in the Jupyter Editor MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

How do I enforce a policy on ipynb_replace_cells_batch? +

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

What risk level is ipynb_replace_cells_batch? +

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

Can I rate-limit ipynb_replace_cells_batch? +

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

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

ipynb_replace_cells_batch is provided by the Jupyter Editor MCP server (jsamuel1/jupyter-editor-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.