Anki MCP Server

Seamlessly integrate Anki with AI assistants through the Model Context Protocol

Beta - This project is in active development. APIs and features may change.

A Model Context Protocol (MCP) server that enables AI assistants to interact with Anki, the spaced repetition flashcard application.

Transform your Anki experience with natural language interaction - like having a private tutor. The AI assistant doesn't just present questions and answers; it can explain concepts, make the learning process more engaging and human-like, provide context, and adapt to your learning style. It can create and edit notes on the fly, turning your study sessions into dynamic conversations. More features coming soon!

Examples and Tutorials

For comprehensive guides, real-world examples, and step-by-step tutorials on using this MCP server with Claude Desktop, visit:

ankimcp.ai - Complete documentation with practical examples and use cases

See docs/ for supplementary documentation, including the reviewer setup guide and the sample Anki deck.

Example Use Cases

Three representative prompts showing the tool flows this server enables:

1. "Help me review my Spanish deck." — The assistant syncs with AnkiWeb (sync), fetches due cards (get_due_cards with deck filter), presents each card (present_card), and records your rating (rate_card). Natural study conversation with explanations tailored to you.

2. "Create 10 Arabic vocab cards with RTL styling." — The assistant lists note types (modelNames), creates a custom RTL model if needed (createModel + updateModelStyling for right-to-left CSS), then batch-creates the cards (addNotes).

3. "Import this image from my Downloads folder into the front of the selected note." — The assistant uploads the local file (storeMediaFile with a file path), reads the currently-selected note from the browser (guiSelectedNotes + notesInfo), and updates the front field with an <img> tag (updateNoteFields).

Available Tools

The server exposes 42 MCP tools — 31 essential tools for everyday Anki operations and 11 GUI tools that drive the Anki desktop interface for note editing/creation workflows.

Essential Tools

Review & Study

• sync - Sync with AnkiWeb to pull latest data and push changes
• get_due_cards - Get cards that are due for review, optionally filtered by deck
• get_cards - Get cards with flexible filtering by state (due, new, learning, suspended, buried) and deck
• present_card - Show a card for review with its question/front side
• rate_card - Rate card performance (Again, Hard, Good, Easy) and schedule the next review

Deck Management

• listDecks - List all decks, optionally with per-deck card-count statistics
• deckStats - Get comprehensive statistics for a single deck (counts, ease/interval distributions)
• createDeck - Create a new empty deck (supports Parent::Child, max 2 levels)
• changeDeck - Move cards to a different deck (created if it doesn't exist)

Note Management

• addNote - Create a single note with specified fields and tags
• addNotes - Batch-create up to 100 notes sharing a deck and model (partial success supported)
• findNotes - Search for notes using Anki query syntax (deck:, tag:, is:due, etc.)
• notesInfo - Get detailed information about notes (fields, tags, CSS styling)
• updateNoteFields - Update existing note fields (CSS-aware, supports HTML content)
• deleteNotes - Delete notes and all associated cards (destructive, requires confirmation)

Tag Management

• getTags - Get all tags in the collection (use first to avoid duplication)
• addTags - Add space-separated tags to specified notes
• removeTags - Remove space-separated tags from specified notes
• replaceTags - Rename a tag across specified notes
• clearUnusedTags - Remove orphaned tags not used by any notes (destructive)

Media Management

• getMediaFilesNames - List media files in collection.media, optionally filtered by pattern
• retrieveMediaFile - Download a media file as base64 content
• storeMediaFile - Upload media from base64 data, an absolute file path, or a URL
• deleteMediaFile - Remove a media file from collection.media (destructive)

💡 Best Practice for Images:

• ✅ Use file paths (e.g., /Users/you/image.png) - Fast and efficient
• ✅ Use URLs (e.g., https://example.com/image.jpg) - Direct download
• ❌ Avoid base64 - Extremely slow and token-inefficient

Just tell Claude where the image is, and it will handle the upload automatically using the most efficient method.

Model/Template Management

• modelNames - List all available note types/models
• modelFieldNames - Get field names for a specific note type
• modelStyling - Get CSS styling information for a note type
• createModel - Create a new note type with custom fields, card templates, and CSS (e.g., RTL models)
• updateModelStyling - Update the CSS styling for an existing note type (applies to all its cards)

Statistics

• collection_stats - Aggregated statistics across all decks with per-deck breakdown
• review_stats - Review history analysis (temporal patterns, retention metrics, study streaks)

GUI Tools

Tools that drive the Anki desktop interface. Intended for note editing/creation and deck-management workflows, not for review sessions.

• guiBrowse - Open the Card Browser and search for cards
• guiSelectCard - Select a specific card in the Card Browser
• guiSelectedNotes - Get IDs of notes currently selected in the Card Browser
• guiAddCards - Open the Add Cards dialog with preset note details
• guiEditNote - Open the note editor for a specific note
• guiDeckOverview - Open the Deck Overview dialog for a specific deck
• guiDeckBrowser - Open the Deck Browser dialog
• guiCurrentCard - Get info about the current card in review mode
• guiShowQuestion - Show the question side of the current card
• guiShowAnswer - Show the answer side of the current card
• guiUndo - Undo the last action in Anki

Prerequisites

• Anki with AnkiConnect plugin installed
• Node.js 22.12.0+

Installation

There are a few ways to get the server onto your machine. Once it's installed, head to Connecting an AI Client to wire it up to your AI assistant — locally or remotely.

npm (global or npx)

The general-purpose way to install the server, suitable for any MCP client that launches it directly.

Install it globally for clients that run the ankimcp command:

npm install -g @ankimcp/anki-mcp-server

Or run it on demand with no install required:

npx @ankimcp/anki-mcp-server

MCPB Bundle (Recommended for Claude Desktop)

The easiest way to install this MCP server for Claude Desktop:

1. Download the latest .mcpb bundle from the Releases page
2. In Claude Desktop, install the extension:
   • Method 1: Go to Settings → Extensions, then drag and drop the .mcpb file
   • Method 2: Go to Settings → Developer → Extensions → Install Extension, then select the .mcpb file
3. Configure AnkiConnect URL if needed (defaults to http://localhost:8765)
4. Restart Claude Desktop

That's it! The bundle includes everything needed to run the server locally.

For Anthropic MCP Directory reviewers: a zero-to-integration walkthrough with a pre-populated sample deck lives in docs/reviewer-setup.md.

Install from Source (for development)

For development or advanced usage:

npm install
npm run build

Connecting an AI Client

There are two ways an AI assistant can reach this server, depending on where the assistant runs:

• Local — the server runs on the same machine as the AI client (Claude Desktop, Cursor, Cline, Zed, or a local browser session). Use STDIO for desktop MCP clients, HTTP for local web-based tools.
• Remote — a hosted/remote AI (e.g. ChatGPT or Claude.ai in the cloud) needs to reach the Anki running on your local machine. Use the managed Tunnel (✅ recommended — authenticated) or, as a lighter-weight unauthenticated alternative, ngrok.

Local

The server runs on the same computer as your AI client and talks to AnkiConnect on localhost.

STDIO (primary local integration)

STDIO is the standard transport for local desktop MCP clients — Claude Desktop, Cursor IDE, Cline, Zed Editor, and others. The client launches the server as a subprocess and communicates over standard input/output.

Supported Clients:

• Claude Desktop
• Cursor IDE - AI-powered code editor
• Cline - VS Code extension for AI assistance
• Zed Editor - Fast, modern code editor
• Other MCP clients that support STDIO transport

For Claude Desktop, the MCPB bundle is the easiest path. For other clients, configure the npm package with the --stdio flag.

Configuration - Choose one method:

Method 1: Using npx (recommended - no installation needed)

{
  "mcpServers": {
    "anki-mcp": {
      "command": "npx",
      "args": ["-y", "@ankimcp/anki-mcp-server", "--stdio"],
      "env": {
        "ANKI_CONNECT_URL": "http://localhost:8765"
      }
    }
  }
}

Method 2: Using global installation

First, install globally:

npm install -g @ankimcp/anki-mcp-server

Then configure:

{
  "mcpServers": {
    "anki-mcp": {
      "command": "ankimcp",
      "args": ["--stdio"],
      "env": {
        "ANKI_CONNECT_URL": "http://localhost:8765"
      }
    }
  }
}

Configuration file locations:

• Cursor IDE: ~/.cursor/mcp.json (macOS/Linux) or %USERPROFILE%\.cursor\mcp.json (Windows)
• Cline: Accessible via settings UI in VS Code
• Zed Editor: Install as MCP extension through extension marketplace

For client-specific features and troubleshooting, consult your MCP client's documentation. See also Connect to Claude Desktop for a config that points directly at a built dist/main-stdio.js.

HTTP (local web-based AI)

HTTP mode runs the server as a local web server speaking the MCP Streamable HTTP protocol. It's the transport a web-based AI tool talks to when pointed at your machine, and it's also what the Remote options expose to the outside world. On its own, HTTP mode binds to localhost only.

Setup - Choose one method:

Method 1: Using npx (recommended - no installation needed)

# Quick start
npx @ankimcp/anki-mcp-server

# With custom options
npx @ankimcp/anki-mcp-server --port 8080 --host 0.0.0.0
npx @ankimcp/anki-mcp-server --anki-connect http://localhost:8765

Method 2: Using global installation

# Install once
npm install -g @ankimcp/anki-mcp-server

# Run the server
ankimcp

# With custom options
ankimcp --port 8080 --host 0.0.0.0
ankimcp --anki-connect http://localhost:8765

Method 3: Install from source (for development)

npm install
npm run build
npm run start:prod:http

To make a local HTTP server reachable by a cloud-hosted AI, use one of the Remote options below.

Remote

A hosted/remote AI (such as ChatGPT or Claude.ai running in the cloud) can't reach localhost directly. These options expose your local Anki to the internet so a remote assistant can talk to it.

Tunnel (✅ Recommended)

Recommended remote path — authenticated & secure. Unlike a raw public port, tunnel mode requires you to log in (OAuth 2.0 device flow), so the endpoint isn't open to anyone who guesses the URL.

Tunnel mode lets web-based AI assistants reach your local Anki without running your own tunnel. The server connects out to the managed AnkiMCP tunnel service (wss://tunnel.ankimcp.ai) over a WebSocket and is assigned a public URL. Authentication is built in — no ngrok account or separate tunnel process required, and you log in once.

Log in (OAuth device flow):

Tunnel mode uses the OAuth 2.0 Device Authorization Grant. Logging in opens your browser automatically to an approval page with the code already embedded in the URL — nothing to type, just approve. (If the browser can't open, the terminal prints a verification URL and code to enter manually as a fallback.) On success, credentials are saved to ~/.ankimcp/credentials.json (file permissions 0600).

# Pre-authenticate (optional — --tunnel will trigger this automatically if needed)
ankimcp --login
npx @ankimcp/anki-mcp-server --login

# Clear saved credentials
ankimcp --logout

Start the tunnel:

# Connect to the managed tunnel service (wss://tunnel.ankimcp.ai)
ankimcp --tunnel
npx @ankimcp/anki-mcp-server --tunnel

# Override the tunnel server URL (must be ws:// or wss://) — e.g. for self-hosting
ankimcp --tunnel wss://my-tunnel.example.com

If no credentials exist, --tunnel automatically starts the login flow first, then continues to the tunnel. This auto-login requires an interactive terminal — when stdout is not a TTY (systemd, headless Docker, CI), the server fast-fails and asks you to run ankimcp --login first. Once connected, the public tunnel URL is printed; press Ctrl+C to disconnect. Share that URL with your AI assistant.

Tunnel-mode environment variables:

The device-flow auth endpoints (/auth/device, /auth/token) are derived from TUNNEL_SERVER_URL, so pointing --tunnel (or TUNNEL_SERVER_URL) at a different host also moves authentication to that host.

How it works: Tunnel mode runs the MCP server in-process behind an in-memory transport (McpModule is started with no built-in transport). TunnelMcpService connects that in-memory transport to the MCP server, and TunnelClient bridges it to the remote tunnel service over a WebSocket — relaying MCP requests in and responses out. AnkiConnect is still only ever reached on your local machine.

ngrok (unauthenticated alternative)

If you'd rather expose local HTTP mode publicly without an account on the managed tunnel, the built-in --ngrok flag launches an ngrok subprocess (src/services/ngrok.service.ts) and prints the public URL in the startup banner:

# One-time ngrok setup, then:
ankimcp --ngrok

This route is unauthenticated — anyone with the URL can reach your Anki, so it's less secure than Tunnel. Prefer Tunnel unless you have a specific reason to manage your own ngrok endpoint. (Requires a global ngrok install and authtoken; the manual two-terminal ngrok http 3000 setup works too.)

CLI Options (all modes)

ankimcp [options]

Options:
  --stdio                        Run in STDIO mode (for MCP clients)
  --tunnel [url]                 Connect via the managed tunnel (authenticated)
  --login                        Authenticate for tunnel mode (OAuth device flow)
  --logout                       Clear saved tunnel credentials
  -p, --port <port>              Port to listen on (HTTP mode, default: 3000)
  -h, --host <host>              Host to bind to (HTTP mode, default: 127.0.0.1)
  -a, --anki-connect <url>       AnkiConnect URL (default: http://localhost:8765)
  --ngrok                        Start ngrok tunnel (requires global ngrok installation)
  --read-only                    Run in read-only mode (blocks all write operations)
  --help                         Show help message

Usage with npx (no installation needed):
  npx @ankimcp/anki-mcp-server                        # HTTP mode
  npx @ankimcp/anki-mcp-server --port 8080            # Custom port
  npx @ankimcp/anki-mcp-server --stdio                # STDIO mode
  npx @ankimcp/anki-mcp-server --tunnel               # Managed tunnel mode
  npx @ankimcp/anki-mcp-server --ngrok                # HTTP mode with ngrok tunnel
  npx @ankimcp/anki-mcp-server --read-only            # Read-only mode

Usage with global installation:
  npm install -g @ankimcp/anki-mcp-server             # Install once
  ankimcp                                             # HTTP mode
  ankimcp --port 8080                                 # Custom port
  ankimcp --stdio                                     # STDIO mode
  ankimcp --tunnel                                    # Managed tunnel mode
  ankimcp --ngrok                                     # HTTP mode with ngrok tunnel
  ankimcp --read-only                                 # Read-only mode

Read-Only Mode (all modes)

The --read-only flag prevents any modifications to your Anki collection. When enabled:

• All read operations work normally (browsing decks, viewing cards, searching notes)
• Review operations are allowed (sync, answerCards, suspend/unsuspend)
• Content modifications are blocked (addNote, deleteNotes, createDeck, updateNoteFields, etc.)
• Useful for safely exploring Anki data without risk of accidental changes

# HTTP mode with read-only
ankimcp --read-only

# STDIO mode with read-only
ankimcp --stdio --read-only

# Can combine with other flags
ankimcp --ngrok --read-only

You can also enable read-only mode via environment variable:

READ_ONLY=true ankimcp

Or in MCP client configuration:

{
  "mcpServers": {
    "anki-mcp": {
      "command": "npx",
      "args": ["-y", "@ankimcp/anki-mcp-server", "--stdio", "--read-only"],
      "env": {
        "ANKI_CONNECT_URL": "http://localhost:8765"
      }
    }
  }
}

Connect to Claude Desktop (Local Mode)

You can configure the server in Claude Desktop by either:

• Going to: Settings → Developer → Edit Config
• Or manually editing the config file

Configuration

Add the following to your Claude Desktop config:

{
  "mcpServers": {
    "anki-mcp": {
      "command": "node",
      "args": ["/path/to/anki-mcp-server/dist/main-stdio.js"],
      "env": {
        "ANKI_CONNECT_URL": "http://localhost:8765"
      }
    }
  }
}

Replace /path/to/anki-mcp-server with your actual project path.

Config File Locations

• macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
• Windows: %APPDATA%\Claude\claude_desktop_config.json
• Linux: ~/.config/Claude/claude_desktop_config.json

For more details, see the official MCP documentation.

Environment Variables (Optional)

Usage Examples

Searching and Updating Notes

# Search for notes in a specific deck
findNotes(query: "deck:Spanish")

# Get detailed information about notes
notesInfo(notes: [1234567890, 1234567891])

# Update a note's fields (HTML content supported)
updateNoteFields(note: {
  id: 1234567890,
  fields: {
    "Front": "<b>¿Cómo estás?</b>",
    "Back": "How are you?"
  }
})

# Delete notes (requires confirmation)
deleteNotes(notes: [1234567890], confirmDeletion: true)

Anki Query Syntax Examples

The findNotes tool supports Anki's powerful query syntax:

• "deck:DeckName" - All notes in a specific deck
• "tag:important" - Notes with the "important" tag
• "is:due" - Cards that are due for review
• "is:new" - New cards that haven't been studied
• "added:7" - Notes added in the last 7 days
• "front:hello" - Notes with "hello" in the front field
• "flag:1" - Notes with red flag
• "prop:due<=2" - Cards due within 2 days
• "deck:Spanish tag:verb" - Spanish deck notes with verb tag (AND)
• "deck:Spanish OR deck:French" - Notes from either deck

Important Notes

CSS and HTML Handling

• The notesInfo tool returns CSS styling information for proper rendering awareness
• The updateNoteFields tool supports HTML content in fields and preserves CSS styling
• Each note model has its own CSS styling - use modelStyling to get model-specific CSS

Update Warning

⚠️ IMPORTANT: When using updateNoteFields, do NOT view the note in Anki's browser while updating, or the fields will not update properly. Close the browser or switch to a different note before updating. See Known Issues for more details.

Deletion Safety

The deleteNotes tool requires explicit confirmation (confirmDeletion: true) to prevent accidental deletions. Deleting a note removes ALL associated cards permanently.

Security

Media File Path and URL Validation

The media tools (storeMediaFile, retrieveMediaFile, deleteMediaFile) and updateNoteFields audio/picture fields include security validation to prevent misuse via prompt injection:

• File path imports are restricted to media file types only (images, audio, video). Non-media files (e.g., SSH keys, credentials, shell configs) are rejected based on MIME type. Configure MEDIA_ALLOWED_TYPES to allow additional file types, or MEDIA_IMPORT_DIR to restrict imports to a specific directory.
• URL imports are validated against SSRF attacks. Requests to private networks (10.x, 172.16.x, 192.168.x), loopback (127.x), link-local (169.254.x), and non-HTTP(S) schemes are blocked. Configure MEDIA_ALLOWED_HOSTS to allow specific private network hosts.
• Filenames are sanitized to prevent path traversal (e.g., ../../ sequences are stripped).

These protections apply to storeMediaFile, retrieveMediaFile, deleteMediaFile, and updateNoteFields audio/picture fields.

Path traversal vulnerability reported by Hideaki Takahashi.

Privacy Policy

This MCP server runs locally on your machine and collects no telemetry, analytics, or usage data.

Full policy: https://ankimcp.ai/privacy/

• Data collection: The server collects nothing. It proxies requests between your AI assistant and your local AnkiConnect plugin.
• Usage / storage: No server-side storage. All flashcard data stays in your Anki installation on your own device.
• Third-party sharing: None. The server only talks to the AnkiConnect URL you configure (default: localhost). If you enable Anki's built-in AnkiWeb sync, that happens between your Anki install and AnkiWeb directly — outside this server's scope.
• Retention: Not applicable — no data is retained server-side.
• Contact: support@ankimcp.ai

Known Issues

For a comprehensive list of known issues and limitations, please visit our documentation:

Known Issues Documentation

Critical Limitations

Note Updates Fail When Viewed in Browser

⚠️ IMPORTANT: When updating notes using updateNoteFields, the update will silently fail if the note is currently being viewed in Anki's browser window. This is an upstream AnkiConnect limitation.

Workaround: Always close the browser or navigate to a different note before updating.

For more details and other known issues, see the full documentation.

Troubleshooting

ERR_REQUIRE_ESM Error

If you see an error like:

Error [ERR_REQUIRE_ESM]: require() of ES Module not supported

This means your Node.js version is not supported. The server requires Node.js 22.12.0+.

Note: The minimum supported runtime is Node.js 22.12.0. Node.js 20 (Iron) reached end-of-life on 2026-04-30 and is no longer supported.

Check your version:

node --version

Solution: Update Node.js to version 22.12.0+. You can download it from nodejs.org or use a version manager like nvm.

Development

Transport Modes

This server supports three MCP transport modes via separate entry points:

STDIO Mode (Default)

• For local MCP clients like Claude Desktop
• Uses standard input/output for communication
• Entry point: dist/main-stdio.js
• Run: npm run start:prod:stdio or node dist/main-stdio.js
• MCPB bundle: Uses STDIO mode

HTTP Mode (Streamable HTTP)

• For remote MCP clients and web-based integrations
• Uses MCP Streamable HTTP protocol
• Entry point: dist/main-http.js
• Run: npm run start:prod:http or node dist/main-http.js
• Default port: 3000 (configurable via PORT env var)
• Default host: 127.0.0.1 (configurable via HOST env var)
• MCP endpoint: http://127.0.0.1:3000/ (root path)

Tunnel Mode (Managed WebSocket Tunnel)

• For web-based AI assistants via the managed AnkiMCP tunnel service, with built-in authentication
• The MCP server runs in-process behind an in-memory transport; TunnelMcpService wires it to the MCP server and TunnelClient bridges it to the tunnel service over a WebSocket
• Entry point: dist/main-tunnel.js
• Run: node dist/main-tunnel.js --tunnel (or ankimcp --tunnel)
• Auth: ankimcp --login / ankimcp --logout; credentials stored at ~/.ankimcp/credentials.json (0600)
• Dev: npm run start:dev:tunnel (watch mode, runs --tunnel --debug)

Building

npm run build  # Builds once, creates dist/ with all three entry points

main-stdio.js, main-http.js, and main-tunnel.js are all built into the same dist/ directory. Choose which to run based on your needs.

HTTP Mode Configuration

Environment Variables:

• PORT - HTTP server port (default: 3000)
• HOST - Bind address (default: 127.0.0.1 for localhost-only)
• ALLOWED_ORIGINS - Comma-separated list of allowed origins for CORS (default: localhost)
• LOG_LEVEL - Logging level (default: info)

Security:

• Origin header validation (prevents DNS rebinding attacks)
• Binds to localhost (127.0.0.1) by default
• No authentication in current version (OAuth support planned)

Example: Running Modes

# Development - STDIO mode (watch mode with auto-rebuild)
npm run start:dev:stdio

# Development - HTTP mode (watch mode with auto-rebuild)
npm run start:dev:http

# Production - STDIO mode
npm run start:prod:stdio
# or
node dist/main-stdio.js

# Production - HTTP mode
npm run start:prod:http
# or
PORT=8080 HOST=0.0.0.0 node dist/main-http.js

Building an MCPB Bundle

To create a distributable MCPB bundle:

npm run mcpb:bundle

This command will:

1. Sync version from package.json to manifest.json
2. Remove old .mcpb files
3. Build the TypeScript project
4. Package dist/ and node_modules/ into an .mcpb file
5. Run mcpb clean to remove devDependencies (optimizes bundle from ~47MB to ~10MB)

The output file will be named anki-mcp-server-X.X.X.mcpb and can be distributed for one-click installation.

What Gets Bundled

The MCPB bundle includes:

• Compiled JavaScript (dist/ directory - includes all three entry points)
• Production dependencies only (node_modules/ - devDependencies removed by mcpb clean)
• Package metadata (package.json)
• Manifest configuration (manifest.json - configured to use main-stdio.js)
• Icon (icon.png)

Source files, tests, and development configs are automatically excluded via .mcpbignore.

Logging in Claude Desktop

When running as an MCPB extension in Claude Desktop, logs are written to:

Log Location: ~/Library/Logs/Claude/ (macOS)

The logs are split across multiple files:

• main.log - General Claude Desktop application logs
• mcp-server-Anki MCP Server.log - MCP protocol messages for this extension
• mcp.log - Combined MCP logs from all servers

Note: The pino logger output (INFO, ERROR, WARN messages from the server code) goes to stderr and appears in the MCP-specific log files. Claude Desktop determines which log file receives which messages, but generally:

• Application startup and MCP protocol communication → MCP-specific log
• Server internal logging (pino) → Both MCP-specific log and sometimes main.log

To view logs in real-time:

tail -f ~/Library/Logs/Claude/mcp-server-Anki\ MCP\ Server.log

Debugging the MCP Server

You can debug the MCP server using the MCP Inspector and attaching a debugger from your IDE (WebStorm, VS Code, etc.).

Note for HTTP Mode: When testing HTTP mode (Streamable HTTP) with MCP Inspector, use "Connection Type: Via Proxy" to avoid CORS errors.

Step 1: Configure Debug Server in MCP Inspector

The mcp-inspector-config.json already includes a debug server configuration:

{
  "mcpServers": {
    "stdio-server-debug": {
      "type": "stdio",
      "command": "node",
      "args": ["--inspect-brk=9229", "dist/main-stdio.js"],
      "env": {
        "MCP_SERVER_NAME": "anki-mcp-stdio-debug",
        "MCP_SERVER_VERSION": "1.0.0",
        "LOG_LEVEL": "debug"
      },
      "note": "Anki MCP server with debugging enabled on port 9229"
    }
  }
}

Step 2: Start the Debug Server

Run the MCP Inspector with the debug server:

npm run inspector:debug

This will start the server with Node.js debugging enabled on port 9229 and pause execution at the first line.

Step 3: Attach Debugger from Your IDE

WebStorm

1. Go to Run → Edit Configurations
2. Add a new Attach to Node.js/Chrome configuration
3. Set the port to 9229
4. Click Debug to attach

VS Code

1. Open the Debug panel (Ctrl+Shift+D / Cmd+Shift+D)
2. Select Debug MCP Server (Attach) configuration
3. Press F5 to attach

Step 4: Set Breakpoints and Debug

Once attached, you can:

• Set breakpoints in your TypeScript source files
• Step through code execution
• Inspect variables and call stack
• Use the debug console for evaluating expressions

The debugger will work with source maps, allowing you to debug the original TypeScript code rather than the compiled JavaScript.

Debugging with Claude Desktop

You can also debug the MCP server while it runs inside Claude Desktop by enabling the Node.js debugger and attaching your IDE.

Step 1: Configure Claude Desktop for Debugging

Update your Claude Desktop config to enable debugging:

macOS: ~/Library/Application Support/Claude/claude_desktop_config.json Windows: %APPDATA%\Claude\claude_desktop_config.json Linux: ~/.config/Claude/claude_desktop_config.json

{
  "mcpServers": {
    "anki-mcp": {
      "command": "node",
      "args": [
        "--inspect=9229",
        "<path_to_project>/anki-mcp-server/dist/main-stdio.js"
      ],
      "env": {
        "ANKI_CONNECT_URL": "http://localhost:8765"
      }
    }
  }
}

Key change: Add --inspect=9229 before the path to dist/main-stdio.js

Debug options:

• --inspect=9229 - Start debugger immediately, doesn't block (recommended)
• --inspect-brk=9229 - Pause execution until debugger attaches (for debugging startup issues)

Step 2: Restart Claude Desktop

After saving the config, restart Claude Desktop. The MCP server will now run with debugging enabled on port 9229.

Step 3: Attach Debugger from Your IDE

WebStorm

1. Go to Run → Edit Configurations
2. Click the + button and select Attach to Node.js/Chrome
3. Configure:
   • Name: Attach to Anki MCP (Claude Desktop)
   • Host: localhost
   • Port: 9229
   • Attach to: Node.js < 8 or Chrome or Node.js > 6.3 (depending on WebStorm version)
4. Click OK
5. Click Debug (Shift+F9) to attach

VS Code

1. Add to .vscode/launch.json:

{
  "version": "0.2.0",
  "configurations": [
    {
      "type": "node",
      "request": "attach",
      "name": "Attach to Anki MCP (Claude Desktop)",
      "port": 9229,
      "skipFiles": ["<node_internals>/**"],
      "sourceMaps": true,
      "outFiles": ["${workspaceFolder}/dist/**/*.js"]
    }
  ]
}

2. Open the Debug panel (Ctrl+Shift+D / Cmd+Shift+D)
3. Select Attach to Anki MCP (Claude Desktop)
4. Press F5 to attach

Step 4: Debug in Real-Time

Once attached, you can:

• Set breakpoints in your TypeScript source files (e.g., src/mcp/primitives/essential/tools/create-model.tool.ts)
• Use Claude Desktop normally - breakpoints will hit when tools are invoked
• Step through code execution
• Inspect variables and call stack
• Use the debug console

Example: Set a breakpoint in create-model.tool.ts at line 119, then ask Claude to create a new model. The debugger will pause at your breakpoint!

Note: The debugger stays attached as long as Claude Desktop is running. You can detach/reattach anytime without restarting Claude Desktop.

Build Commands

npm run build              # Build the project (compile TypeScript to JavaScript)
npm run start:dev:stdio    # STDIO mode with watch (auto-rebuild)
npm run start:dev:http     # HTTP mode with watch (auto-rebuild)
npm run type-check         # Run TypeScript type checking
npm run lint               # Run ESLint
npm run mcpb:bundle        # Sync version, clean, build, and create MCPB bundle

NPM Package Testing (Local)

Test the npm package locally before publishing:

# 1. Create local package
npm run pack:local         # Builds and creates @ankimcp/anki-mcp-server-*.tgz

# 2. Install globally from local package
npm run install:local      # Installs from ./@ankimcp/anki-mcp-server-*.tgz

# 3. Test the command
ankimcp                    # Runs HTTP server on port 3000

# 4. Uninstall when done testing
npm run uninstall:local    # Removes global installation

How it works:

• npm pack creates a .tgz file identical to what npm publish would create
• Installing from .tgz simulates what users get from npm install -g ankimcp
• This lets you test the full user experience before publishing to npm

Testing Commands

npm test              # Run all tests
npm run test:unit     # Run unit tests only
npm run test:tools    # Run tool-specific tests
npm run test:workflows # Run workflow integration tests
npm run test:e2e      # Run end-to-end tests
npm run test:cov      # Run tests with coverage report
npm run test:watch    # Run tests in watch mode
npm run test:debug    # Run tests with debugger
npm run test:ci       # Run tests for CI (silent, with coverage)

Test Coverage

The project maintains 70% minimum coverage thresholds for:

• Branches
• Functions
• Lines
• Statements

Coverage reports are generated in the coverage/ directory.

Versioning

This project follows Semantic Versioning with a pre-1.0 development approach:

• 0.x.x - Beta/Development versions (current phase)

  • 0.1.x - Bug fixes and patches
  • 0.2.0+ - New features or minor improvements
  • Breaking changes are acceptable in 0.x versions

• 1.0.0 - First stable release

  • Will be released when the API is stable and tested
  • Breaking changes will require major version bumps (2.0.0, etc.)

Current Status: 0.19.0 - Active beta development. Recent features include batch note creation (addNotes), integrated ngrok tunneling (--ngrok flag), media file management, model/template management, and comprehensive deck statistics. APIs may change based on feedback and testing.

MCPB spec evolution

This project targets Anthropic's MCPB bundle specification, which is still evolving. We track the spec at https://github.com/modelcontextprotocol/mcpb and may introduce breaking changes to stay compliant. Breaking changes are permitted under the 0.x.x versioning scheme.

Similar Projects

If you're exploring Anki MCP integrations, here are other projects in this space:

scorzeth/anki-mcp-server

• Status: Appears to be abandoned (no recent updates)
• Early implementation of Anki MCP integration

nailuoGG/anki-mcp-server

• Approach: Lightweight, single-file implementation
• Architecture: Procedural code structure with all tools in one file
• Good for: Simple use cases, minimal dependencies

Why this project differs:

• Enterprise-grade architecture: Built on NestJS with dependency injection
• Modular design: Each tool is a separate class with clear separation of concerns
• Maintainability: Easy to extend with new features without touching existing code
• Testing: Comprehensive test suite with 70% coverage requirement
• Type safety: Strict TypeScript with Zod validation
• Error handling: Robust error handling with helpful user feedback
• Production-ready: Proper logging, progress reporting, and MCPB bundle support
• Scalability: Can easily grow from basic tools to complex workflows

Use case: If you need a solid foundation for building advanced Anki integrations or plan to extend functionality significantly, this project's architectural approach makes it easier to maintain and scale over time.

Useful Links

• Model Context Protocol Documentation
• AnkiConnect API Documentation
• Claude Desktop Download
• Building Desktop Extensions (Anthropic Blog)
• MCP Servers Repository
• NestJS Documentation
• Anki Official Website

License & Attribution

This project is licensed under the MIT License — see LICENSE for the full text.

Copyright © 2026 Anatoly Tarnavsky.

Third-Party Attributions

• Anki® is a registered trademark of Ankitects Pty Ltd. This project is an unofficial third-party tool and is not affiliated with, endorsed by, or sponsored by Ankitects Pty Ltd. The Anki logo is used under the alternative license for referencing Anki with a link to https://apps.ankiweb.net. For the official Anki application, visit https://apps.ankiweb.net.

• Model Context Protocol (MCP) is an open standard by Anthropic. The MCP logo is from the official MCP documentation repository and is used under the MIT License. For more information about MCP, visit https://modelcontextprotocol.io.

• This is an independent project that bridges Anki and MCP technologies. All trademarks, service marks, trade names, product names, and logos are the property of their respective owners.