Integrations
Enables programmatic interaction with Anki decks, including listing decks, viewing cards, adding new cards, reviewing with spaced repetition, and specialized functionality for Japanese vocabulary learning with sample sentences.
Japanese Vocab Anki MCP Server
A Model Context Protocol server implementation for interacting with Anki decks programmatically. This server allows Language Models to interact with Anki through a standardized interface, with special support for Japanese language learning.
This is vibe-coded with Cursor with Claude 3.5 Sonnet.
Features
- List available decks
- View cards in decks
- Add new cards
- Review cards with spaced repetition
- Import Japanese vocabulary with readings and meanings
- Add sample sentences to Japanese vocabulary cards
- Track review history and learning progress
End-to-End Example: Japanese Vocabulary Study with Claude
Here's a complete workflow showing how to use Claude to enhance your Japanese vocabulary cards with sample sentences.
Step 1: Generate Fill-in-the-Blank Exercises
First, ask Claude to create practice exercises using the study_japanese_vocab_prompt
:
Claude will look through your recently reviewed vocabulary and create contextual sentences with blanks to test your understanding.
Step 2: Convert to Sample Sentences
Next, use the vocab_sentences_json_prompt
to convert these sentences into a structured format:
Claude will transform the sentences into a JSON dictionary mapping each vocabulary word to its sample sentences.
Step 3: Update Anki Cards
Finally, use the update_notes_with_sentences
tool to add these sentences to your Anki cards:
The sentences will be added to the reading field of each vocabulary card, providing more context for your studies.
Results in Anki
After the update, your cards will include the new sample sentences:
This workflow helps you:
- Practice vocabulary in context through fill-in-the-blank exercises
- Add natural example sentences to your cards
- Build a more comprehensive understanding of each word's usage
Installation
- Clone this repository:
Usage
- Make sure Anki is not running (to avoid database locks)
- Set the path to your Anki collection (optional):
- Run the server:
Available Resources
anki://decks
- List all available Anki decksanki://deck/{deck_name}/cards
- List all cards in a specific deckanki://recent/reviewed
- View cards reviewed in the last 24 hoursanki://recent/learned
- View cards learned (graduated from new) in the last 24 hours
Available Tools
Basic Card Management
add_card(deck_name: str, front: str, back: str)
- Add a new card to a deckreview_card(card_id: int, ease: int)
- Review a card with a specific ease (1-4)get_card_history(card_id: int)
- Get detailed review history for a specific card
Japanese Vocabulary Features
import_japanese_vocab(csv_path: str, deck_name: str, tags: str = None)
- Import Japanese vocabulary from CSVupdate_notes_with_sentences(vocab_sentences: Dict[str, List[str]], deck_name: str = "Try! N3 Vocab")
- Add sample sentences to vocabulary notes
Review History
get_deck_review_history(deck_name: str)
- Get review history for all cards in a deck within the past 24 hours
Available Prompts
create_deck_prompt(deck_name: str)
- Get help creating a new deckreview_history_prompt()
- Get help analyzing review historystudy_japanese_vocab_prompt()
- Get help with Japanese vocabulary studyvocab_sentences_json_prompt()
- Generate JSON dictionary mapping vocab to sample sentences
Japanese Note Type Requirements
The server expects a note type called "Japanese (recognition)" with the following fields:
- Expression (Japanese word)
- Meaning (English meaning)
- Reading (with furigana and sample sentences)
License
MIT License
This server cannot be installed
local-only server
The server can only run on the client's local machine because it depends on local resources.
A Model Context Protocol server that enables language models to interact with Anki flashcard decks programmatically, with specialized features for Japanese language learning including vocabulary import, sample sentence generation, and spaced repetition review.
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