Anki MCP Server

The Anki MCP server bridges the gap between conversational AI assistants and the powerful spaced‑repetition system that is Anki. By exposing a set of intuitive resources, tools, and queries over the Model Context Protocol, it allows an AI assistant—such as Claude—to seamlessly manage flashcard decks without leaving the chat interface. This integration solves a common developer pain point: automating study workflows while keeping data locally secure and under user control.

At its core, the server connects to a locally running Anki desktop instance through the Anki‑Connect add‑on. It exposes search resources that mirror familiar Anki query syntax, enabling the assistant to fetch cards from the current deck (), due cards ready for review (), or entirely new items (). These resources provide quick, read‑only access to the underlying card pool and can be combined with filtering or pagination logic in the client.

Beyond read‑only access, the server offers a suite of tools that modify Anki’s state. The tool lets the assistant record a user’s response, assigning an ease rating that influences future scheduling. creates new flashcards directly in the default deck, allowing dynamic content generation from conversational context. and provide controlled batch retrieval, useful for building review sessions or curating study sets. All inputs are simple JSON structures, making the API straightforward to invoke from any MCP‑compatible client.

Developers can weave these capabilities into richer AI workflows. For example, a study assistant could prompt the user with a question, capture their answer through the chat, and immediately record the result in Anki. A tutoring bot could generate new cards on the fly from user‑generated content, ensuring that learning material is always up to date. Because the server runs locally and communicates over standard input/output, it preserves user privacy while offering low‑latency interactions suitable for real‑time dialogue.

What sets the Anki MCP server apart is its tight coupling with Anki’s native scheduling algorithm and its minimal configuration footprint. By leveraging the existing Anki‑Connect add‑on, it sidesteps the need for custom database drivers or API keys. The server’s resource URLs mimic Anki’s own query language, reducing the learning curve for developers familiar with the desktop app. Together, these design choices provide a powerful yet lightweight bridge that empowers AI assistants to deliver personalized, spaced‑repetition‑based learning experiences directly within conversational contexts.