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What kernel_status does on Kaggle-MCP
AI agents call kernel_status to retrieve information from Kaggle-MCP without modifying anything. It is typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
Why kernel_status is rated Low
The tool retrieves information about a kernel's current state without modifying, executing, or deleting anything. It is a simple read operation similar to checking metadata. The fact that it operates on Kaggle kernels (which are compute environments) does not change the classification, as the tool itself only observes status rather than triggering execution or making changes.
From the tool's definition Tool name and description explicitly indicate a status query: "Get the status of a kernel." This is a retrieval operation with no modification, execution, or deletion of data.
Attacks that exploit this kind of access
The rule that runs kernel_status safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Kaggle-MCP, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For kernel_status, this is the rule to start with:
kernel_status is read-only, so it stays allowed. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect Kaggle-MCP, apply this rule, and every kernel_status call is checked against it from then on.
Questions about kernel_status
Get the status of a kernel. It is categorised as a Read tool in the Kaggle-MCP MCP Server, which means it retrieves data without modifying state.
Register the Kaggle MCP server in PolicyLayer and add a rule for kernel_status: 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 Kaggle-MCP. Nothing to install.
kernel_status 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 kernel_status 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 kernel_status. 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.
kernel_status is provided by the Kaggle MCP server (54yyyu/kaggle-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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