List synchronized notebook files visible through the configured Drive access.
AI agents call list_drive_notebooks to retrieve information from Pypi:colab Drive without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool queries and returns a list of notebooks from Google Drive without creating, modifying, or deleting any data. It has no side effects beyond information disclosure. The blast radius is minimal—an agent cannot cause damage by merely listing files, though it may inform what files exist for subsequent operations.
From the tool's definition Tool name is 'list_drive_notebooks' and description states 'List synchronized notebook files visible through the configured Drive access.' The verb 'list' and the read-only nature of enumerating files without modification confirm this is a retrieval operation.
Attacks that exploit this kind of access
List synchronized notebook files visible through the configured Drive access. It is categorised as a Read tool in the Pypi:colab Drive MCP Server, which means it retrieves data without modifying state.
Register the Pypi:colab Drive MCP server in PolicyLayer and add a rule for list_drive_notebooks: 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.
list_drive_notebooks is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the list_drive_notebooks 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.
Set action: deny in the PolicyLayer policy for list_drive_notebooks. 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.
list_drive_notebooks 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.
Every MCP server has a record like this.
Type a name, get the same breakdown: verified identity, auth posture, risk grade, capabilities, recommended policy.
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