List common Jupyter Notebook kernel configurations.
AI agents call ipynb_list_available_kernels to retrieve information from Jupyter Editor without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool performs a read-only operation to enumerate kernel configurations. It has no side effects, does not modify state, and does not execute code or trigger external operations. The blast radius of misuse is minimal—an agent gaining this information cannot directly cause harm, though it could be used for reconnaissance.
From the tool's definition Tool name 'ipynb_list_available_kernels' and description 'List common Jupyter Notebook kernel configurations' indicate a query/list operation that retrieves configuration data without modifying or executing anything.
Attacks that exploit this kind of access
List common Jupyter Notebook kernel configurations. It is categorised as a Read tool in the Jupyter Editor MCP Server, which means it retrieves data without modifying state.
Register the Jupyter Editor MCP server in PolicyLayer and add a rule for ipynb_list_available_kernels: 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 Jupyter Editor. Nothing to install.
ipynb_list_available_kernels 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 ipynb_list_available_kernels 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 ipynb_list_available_kernels. 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.
ipynb_list_available_kernels is provided by the Jupyter Editor MCP server (jsamuel1/jupyter-editor-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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