Get summary information about a Jupyter Notebook (.ipynb).
AI agents call ipynb_get_notebook_info 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 query operation on notebook metadata. It retrieves and returns information about a notebook's structure and properties without side effects, reversible modifications, code execution, or data destruction. The verb 'Get' and absence of any modification or execution semantics clearly place it in the Read category with low severity.
From the tool's definition Tool name 'ipynb_get_notebook_info' and description 'Get summary information about a Jupyter Notebook (.ipynb)' indicate a retrieval operation that returns metadata or overview data without modifying, executing, or deleting notebook content.
Attacks that exploit this kind of access
Get summary information about a Jupyter Notebook (.ipynb). 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_get_notebook_info: 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_get_notebook_info 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_get_notebook_info 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_get_notebook_info. 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_get_notebook_info 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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