get_cells_info

THE RISK

Low Risk

Why get_cells_info needs a policy

This tool retrieves and queries cell information with no side effects. It does not modify data, execute code, delete content, or affect external systems. It is a straightforward read operation analogous to listing or fetching metadata. The low severity reflects minimal blast radius even if misused by an AI agent.

From the tool's definition Tool name is 'get_cells_info' and description states 'Get information about all cells in the notebook' — retrieves metadata about notebook cells without modifying or executing them.

Documented attack patterns abuse exactly the kind of access get_cells_info gives an agent:

POLICY

How to control get_cells_info

PolicyLayer is an MCP gateway — it sits between your AI agents and JupyterMCP, and nothing reaches the server without passing your rules. This is the rule we recommend for get_cells_info:

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "get_cells_info": {}
  }
}

get_cells_info is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.

Create a free account and register JupyterMCP — nothing to install.
Add this policy — paste it, or build it visually.
Point your MCP client (Claude, Cursor, anything) at your gateway URL.

CAP THIS TOOL →

Free to start. No card required.

EXPLORE

Related tools and policies

More JupyterMCP tools

Execute run_all_cells Restart and run all cells in the notebook. You need to wait for user approval Execute run_cell Run a specific cell by its index Args: index: The index of the cell to ru Execute edit_cell_content Edit the content of a specific cell by its index and optionally execute it Args: Execute insert_and_execute_cell Insert a cell at the specified position and execute it, and optionally set slideshow type. Write save_notebook Save the current Jupyter notebook Write set_slideshow_type set_slideshow_type Read get_cell_text_output Get the text output content of a specific code cell by its index Args: in Read get_image_output Get image outputs from a specific cell by its index Args: index: The inde

All 11 JupyterMCP tools →

Read tools on other servers

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Go deeper

The MCP Attack Database → Documented attack patterns against MCP deployments — and the policies that stop them.
Data exfiltration → How read access becomes an exfiltration channel when chained with untrusted content.
MCP token cost → What connecting this server costs in context-window tokens on every request.
Rate Limiting MCP Tool Calls: A Practical Guide →
MCP Security: Why Prompt Guardrails Aren't Enough →

FAQ

Questions about get_cells_info

What does the get_cells_info tool do? +

Get information about all cells in the 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 get_cells_info? +

Register the Jupyter MCP server in PolicyLayer and add a rule for get_cells_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 JupyterMCP. Nothing to install.

What risk level is get_cells_info? +

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

Can I rate-limit get_cells_info? +

Yes. Add a rate_limit block to the get_cells_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.

How do I block get_cells_info completely? +

Set action: deny in the PolicyLayer policy for get_cells_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.

What MCP server provides get_cells_info? +

get_cells_info is provided by the Jupyter MCP server (jjsantos01/jupyter-notebook-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every JupyterMCP tool call.

Start from JupyterMCP, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.

CHECK YOUR STACK →