kernel_status

Get the current status and Python interpreter of the kernel for a notebook.

Server JupyterMCP try3d/jupytermcp
Category Read
Risk class Low
Parameters 00 required

What kernel_status does on JupyterMCP

AI agents call kernel_status to retrieve information from JupyterMCP without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.

Why kernel_status needs a policy

This tool retrieves kernel status and metadata (status, Python interpreter version) without executing code, modifying the kernel, or having side effects. It is purely informational, fitting the Read category for data retrieval operations.

From the tool's definition Tool name 'kernel_status' and description 'Get the current status and Python interpreter of the kernel' indicate a query operation that retrieves information without modifying state.

Questions about kernel_status

What does the kernel_status tool do? +

Get the current status and Python interpreter of the kernel for a notebook. It is categorised as a Read tool in the JupyterMCP MCP Server, which means it retrieves data without modifying state.

How do I enforce a policy on kernel_status? +

Register the Jupyter 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 JupyterMCP. Nothing to install.

What risk level is kernel_status? +

kernel_status is a Read tool with low risk. Read-only tools are generally safe to allow by default.

Can I rate-limit kernel_status? +

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.

How do I block kernel_status completely? +

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.

What MCP server provides kernel_status? +

kernel_status is provided by the Jupyter MCP server (try3d/jupytermcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

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