This record as markdown: /tools/io-github-arielbk-anki-mcp/gui-show-answer.md
What gui_show_answer does on Anki
AI agents invoke gui_show_answer 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 gui_show_answer is rated High
Based on the tool name and context of sibling tools (gui_answer_card, gui_current_card), this tool likely triggers a GUI operation in Anki to display the answer side of the current flashcard. This constitutes an Execute action as it triggers an external UI operation. Confidence is low due to the empty description.
From the tool's definition Tool name 'gui_show_answer' suggests triggering a GUI action in Anki to reveal a card's answer; description is empty and uninformative.
Attacks that exploit this kind of access
The rule that runs gui_show_answer 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 gui_show_answer, this is the rule to start with:
gui_show_answer 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 gui_show_answer call is checked against it from then on.
Questions about gui_show_answer
gui_show_answer 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 gui_show_answer: 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.
gui_show_answer 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 gui_show_answer 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 gui_show_answer. 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.
gui_show_answer 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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