This record as markdown: /tools/io-github-arielbk-anki-mcp/reload-collection.md
What reload_collection does on Anki
AI agents invoke reload_collection to trigger actions in Anki. What it does depends on the arguments the agent supplies, and its effects often reach beyond the immediate call: builds kicked off, notifications sent, workflows started.
Why reload_collection is rated High
The name 'reload_collection' suggests reloading/refreshing the Anki card collection, which would trigger an external operation on the Anki application. This could be a Read-adjacent action (refreshing data) or an Execute action (triggering a reload in the Anki process). Given the empty description, confidence is low.
From the tool's definition Tool name: reload_collection; description is empty and uninformative.
Attacks that exploit this kind of access
The rule that runs reload_collection safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Anki, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For reload_collection, this is the rule to start with:
reload_collection stays usable, but rate-capped: a runaway agent can't fire it dozens of times a minute. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect Anki, apply this rule, and every reload_collection call is checked against it from then on.
Questions about reload_collection
reload_collection is a execute tool on the Anki MCP server. It is categorised as a Execute tool in the Anki MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Anki MCP server in PolicyLayer and add a rule for reload_collection: 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.
reload_collection is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.
Yes. Add a rate_limit block to the reload_collection 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 reload_collection. 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.
reload_collection is provided by the Anki MCP server (@arielbk/anki-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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