anki-mcp-server-addon by ankimcp - MCP Server

AnkiMCP Server (Addon)

An Anki addon that exposes your collection to AI assistants via the Model Context Protocol (MCP).

What is this?

AnkiMCP Server runs a local MCP server inside Anki, allowing AI assistants like Claude to interact with your flashcard collection. This enables AI-powered study sessions, card creation, and collection management.

Part of the ankimcp.ai project.

Note on First Run

On first run, this addon downloads pydantic_core (~2MB) from PyPI. This is required because pydantic_core contains platform-specific binaries (Windows/macOS/Linux) that cannot be bundled in a single addon file.

Features

Local HTTP server - Runs on http://127.0.0.1:3141/ by default
MCP protocol - Compatible with any MCP client (Claude Desktop, etc.)
Auto-start - Server starts automatically when Anki opens
Tunnel-friendly - Works with Cloudflare Tunnel, ngrok, etc.
Cross-platform - Works on macOS, Windows, and Linux (x64 and ARM)

Installation

From AnkiWeb (recommended)

Open Anki and go to Tools → Add-ons → Get Add-ons...
Enter code: 124672614
Restart Anki

From GitHub Releases

Download anki_mcp_server.ankiaddon from Releases
Double-click to install, or use Tools → Add-ons → Install from file...
Restart Anki

Usage

The server starts automatically when you open Anki. Check status via Tools → AnkiMCP Server Settings...

Connect with Claude Desktop

Add to your Claude Desktop config (~/Library/Application Support/Claude/claude_desktop_config.json on macOS):

{
  "mcpServers": {
    "anki": {
      "url": "http://127.0.0.1:3141/"
    }
  }
}

Configuration

Edit via Anki's Tools → Add-ons → AnkiMCP Server → Config:

{
  "mode": "http",
  "http_port": 3141,
  "http_host": "127.0.0.1",
  "http_path": "",
  "cors_origins": [],
  "cors_expose_headers": ["mcp-session-id", "mcp-protocol-version"],
  "auto_connect_on_startup": true
}

Custom Path

Set http_path to serve the MCP endpoint under a custom path. Useful when exposing Anki via a tunnel (Cloudflare, ngrok) to avoid a fully open endpoint:

{
  "http_path": "my-secret-path"
}

The server will be accessible at http://localhost:3141/my-secret-path/ instead of the root. Leave empty for default behavior.

CORS Configuration

To allow browser-based MCP clients (like web-hosted MCP Inspector), add allowed origins:

{
  "cors_origins": ["https://inspector.example.com", "http://localhost:5173"]
}

Use ["*"] to allow all origins (not recommended for production).

The cors_expose_headers setting controls which response headers browsers can read. The defaults (mcp-session-id, mcp-protocol-version) are required for the MCP Streamable HTTP protocol to work in browsers.

Available Tools

Essential Tools

Tool	Description
`sync`	Synchronize collection with AnkiWeb
`list_decks`	List all decks in the collection
`create_deck`	Create a new deck
`find_notes`	Search for notes using Anki's search syntax
`notes_info`	Get detailed information about notes
`add_note`	Add a new note to a deck
`card_management`	Manage cards: `reposition` (set learning order), `changeDeck` (move between decks), `bury` (hide until tomorrow), `unbury` (restore buried cards in a deck)
`update_note_fields`	Update fields of existing notes
`delete_notes`	Delete notes from the collection
`get_due_cards`	Get next due card for review (supports `skip_images`/`skip_audio` for voice mode)
`present_card`	Get card content for review
`rate_card`	Rate a card after review (Again/Hard/Good/Easy)
`model_names`	List available note types
`model_field_names`	Get field names and descriptions for a note type
`model_styling`	Get CSS styling for a note type
`update_model_styling`	Update CSS styling for a note type
`create_model`	Create a new note type
`store_media_file`	Store a media file (image/audio)
`get_media_files_names`	List media files matching a pattern
`delete_media_file`	Delete a media file

FSRS Tools

Tool	Description
`get_fsrs_params`	Get FSRS scheduler parameters for deck presets
`set_fsrs_params`	Update FSRS parameters (weights, desired retention, max interval)
`get_card_memory_state`	Get FSRS memory state (stability, difficulty, retrievability) for cards
`optimize_fsrs_params`	Run FSRS parameter optimization using Anki's built-in optimizer

GUI Tools

These tools interact with Anki's user interface:

Tool	Description
`gui_browse`	Open the card browser with a search query
`gui_add_cards`	Open the Add Cards dialog
`gui_edit_note`	Open the note editor for a specific note
`gui_current_card`	Get info about the currently displayed card
`gui_show_question`	Show the question side of current card
`gui_show_answer`	Show the answer side of current card
`gui_select_card`	Select a specific card in the reviewer
`gui_deck_browser`	Navigate to deck browser
`gui_undo`	Undo the last operation

Resources

Resource	URI	Description
`system_info`	`anki://system-info`	Anki version, profile, and scheduler info
`query_syntax`	`anki://query-syntax`	Anki search query syntax reference
`schema`	`anki://schema`	Data model documentation (entities, fields, relationships)
`stats_today`	`anki://stats/today`	Today's study statistics
`stats_forecast`	`anki://stats/forecast`	30-day review forecast
`stats_collection`	`anki://stats/collection`	Overall collection statistics
`fsrs_config`	`anki://fsrs/config`	FSRS configuration summary and parameters

Prompts

Prompt	Description
`review_session`	Guided review session workflow (interactive, quick, or voice mode)

Requirements

Anki 25.07 or later (ships Python 3.13)
Anki 25.02 and earlier ship Python 3.9, which is not supported — the MCP SDK requires Python 3.10+ (#8)

Architecture

The addon runs an MCP server in a background thread with HTTP transport (FastMCP + uvicorn). All Anki operations are bridged to the main Qt thread via a queue system, following the same proven pattern as AnkiConnect.

For details, see Anki Add-on Development Documentation.

Development

Running E2E Tests

E2E tests run against a real Anki instance in Docker using headless-anki.

# Install test dependencies
python -m venv .venv
source .venv/bin/activate
pip install -r requirements-dev.txt

# Build the addon
./package.sh

# Start Anki container
cd .docker && docker compose up -d && cd ..

# Run tests (waits for server automatically)
pytest tests/e2e/ -v

# Stop container
cd .docker && docker compose down

Or use the Makefile shortcuts:

make e2e        # Build, start container, run tests, stop
make e2e-up     # Just start container
make e2e-test   # Just run tests
make e2e-down   # Just stop container

CI

E2E tests run automatically on push to any branch and on PRs to main. See .github/workflows/e2e.yml.

License

AGPL-3.0-or-later

ankimcp/anki-mcp-server-addon