AI agents call search_notes to retrieve information from Anki without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool retrieves and queries existing data from Anki without side effects. It is a straightforward search/filter operation that does not create, modify, delete, or execute arbitrary code. The presence of sibling destructive tools (delete_note, delete_notes_batch) confirms this is the read-only counterpart.
From the tool's definition Tool description explicitly states 'Search existing notes' with filters applied; no modifications, deletions, or destructive operations mentioned. Returns query results only.
Attacks that exploit this kind of access
Search existing notes by Anki query, note type, deck, or tag filters. It is categorised as a Read tool in the Anki MCP Server, which means it retrieves data without modifying state.
Register the Anki MCP server in PolicyLayer and add a rule for search_notes: 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 Anki. Nothing to install.
search_notes 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 search_notes 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 search_notes. 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.
search_notes is provided by the Anki MCP server (yama662607/anki-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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