update_local_cell · Pypi:colab Drive MCP: Risk & Policy

WHAT IT DOES

What update_local_cell does on Pypi:colab Drive

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

WHY IT NEEDS A POLICY

Why update_local_cell needs a policy

This tool modifies cell content and metadata (source code and cell type) within a notebook, making it a Write operation. Severity is medium because while modifications are reversible (the user can undo or re-edit), incorrect cell updates in a notebook could cause logic errors, loss of code, or broken workflows.

From the tool's definition Tool description states 'Replace a cell's source and optionally its type' — a clear modification operation. The function name 'update_local_cell' also indicates write/edit behavior.

Attacks that exploit this kind of access

Recommended rule Ready

Verdict

update_local_cell Rate-limited

update_local_cell 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": {
    "update_local_cell": {
      "limits": [
        {
          "counter": "update_local_cell_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 Pypi:colab Drive, so you can run agents against it safely.

FAQ

Questions about update_local_cell

What does the update_local_cell tool do? +

Replace a cell's source and optionally its type. It is categorised as a Write tool in the Pypi:colab Drive MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

How do I enforce a policy on update_local_cell? +

Register the Pypi:colab Drive MCP server in PolicyLayer and add a rule for update_local_cell: 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 Pypi:colab Drive. Nothing to install.

What risk level is update_local_cell? +

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

Can I rate-limit update_local_cell? +

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

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

update_local_cell is provided by the Pypi:colab Drive MCP server (yummytastycode/colab-drive-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

// THE FULL RECORD

update_local_cell is one line of Pypi:colab Drive's registry record.

The record carries the whole server: verified identity, auth posture, risk grade, every tool classified, recommended policy — re-checked continuously.

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