colab_cancel
AI agents call colab_cancel to permanently remove resources in Mcp Colab Gpu — typically in cleanup and lifecycle workflows. It does its job in a single call, and there is no undo.
The name 'colab_cancel' strongly implies cancelling/terminating a running Colab job or execution. Cancelling a running job is typically irreversible — the job's in-progress work is lost and cannot be resumed. This aligns with Destructive (irreversible action). However, the empty description lowers confidence, as the tool could conceivably be a softer stop operation.
From the tool's definition Tool name 'colab_cancel' on a server that runs Python code on GPU/TPU runtimes; description is empty.
Attacks that exploit this kind of access
colab_cancel. It is categorised as a Destructive tool in the Mcp Colab Gpu MCP Server, which means it can permanently delete or destroy data. Block by default and require explicit approval.
Register the Mcp Colab Gpu MCP server in PolicyLayer and add a rule for colab_cancel: 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 Mcp Colab Gpu. Nothing to install.
colab_cancel is a Destructive tool with critical risk. Critical-risk tools should be blocked by default and only enabled with explicit human approval.
Yes. Add a rate_limit block to the colab_cancel 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 colab_cancel. 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.
colab_cancel is provided by the Mcp Colab Gpu MCP server (mio-github/mcp-colab-gpu). 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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