clear_local_outputs · Pypi:colab Drive MCP: Risk & Policy

WHAT IT DOES

What clear_local_outputs does on Pypi:colab Drive

AI agents use clear_local_outputs 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 clear_local_outputs needs a policy

This tool modifies a local notebook by removing output data and execution counts. While it deletes content (outputs), this is a reversible operation in the context of notebooks since outputs can be regenerated by re-running cells. It is a Write operation as it modifies the notebook file, not a Destructive one since the notebook structure and code remain intact and outputs can be recreated.

From the tool's definition Clear outputs and execution counts from a local notebook

Attacks that exploit this kind of access

Recommended rule Ready

Verdict

clear_local_outputs Rate-limited

clear_local_outputs 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": {
    "clear_local_outputs": {
      "limits": [
        {
          "counter": "clear_local_outputs_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 clear_local_outputs

What does the clear_local_outputs tool do? +

Clear outputs and execution counts from a local notebook. 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 clear_local_outputs? +

Register the Pypi:colab Drive MCP server in PolicyLayer and add a rule for clear_local_outputs: 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 clear_local_outputs? +

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

Can I rate-limit clear_local_outputs? +

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

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

clear_local_outputs 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.