AI agents call find_in_notebook to retrieve information from Ast Editor without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
Based on the tool name 'find_in_notebook', this appears to be a search or query function that retrieves data from a notebook without modifying it. The lack of verbs like 'edit', 'delete', 'create', or 'execute' suggests a non-destructive, non-modifying operation.
From the tool's definition Tool name 'find_in_notebook' suggests a search/query operation. The description is empty, which reduces confidence. However, the name implies retrieval or searching of data within a notebook, consistent with Read category operations.
Documented attack patterns abuse exactly the kind of access find_in_notebook gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Ast Editor, and nothing reaches the server without passing your rules. This is the rule we recommend for find_in_notebook:
{
"version": "1",
"default": "deny",
"tools": {
"find_in_notebook": {}
}
}find_in_notebook is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.
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find_in_notebook. It is categorised as a Read tool in the Ast Editor MCP Server, which means it retrieves data without modifying state.
Register the Ast Editor MCP server in PolicyLayer and add a rule for find_in_notebook: 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 Ast Editor. Nothing to install.
find_in_notebook 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 find_in_notebook 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 find_in_notebook. 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.
find_in_notebook is provided by the Ast Editor MCP server (kambleakash0/agent-skills). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Ast Editor, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
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59 Ast Editor tools catalogued and risk-classified — across an index of 43,000+ MCP servers.