AI agents call get_cells to retrieve information from Marimo without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool queries and returns notebook cell metadata and code without side effects. It is a straightforward data retrieval operation that fits the Read category. Severity is low because viewing notebook contents poses minimal risk even if misused by an AI agent.
From the tool's definition Tool name is 'get_cells' and description states it retrieves 'all cells with their IDs, code, and runtime state' — a pure data retrieval operation with no modification, deletion, or execution of code.
Attacks that exploit this kind of access
Get all cells with their IDs, code, and runtime state. It is categorised as a Read tool in the Marimo MCP Server, which means it retrieves data without modifying state.
Register the Marimo MCP server in PolicyLayer and add a rule for get_cells: 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 Marimo. Nothing to install.
get_cells 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 get_cells 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 get_cells. 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.
get_cells is provided by the Marimo MCP server (vladisluv12/marimo-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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