Anki MCP
A MCP server that enables AI assistants to interact with Anki, the spaced repetition flashcard application.
Anki MCP Desktop
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
Available Tools
Review & Study
sync- Sync with AnkiWebget_due_cards- Get cards for reviewpresent_card- Show card for reviewrate_card- Rate card performance
Deck Management
list_decks- Show available deckscreateDeck- Create new decks
Note Management
addNote- Create new notesfindNotes- Search for notes using Anki query syntaxnotesInfo- Get detailed information about notes (fields, tags, CSS)updateNoteFields- Update existing note fields (CSS-aware, supports HTML)deleteNotes- Delete notes and their cards
Media Management
mediaActions- Manage media files (audio/images)storeMediaFile- Upload media from base64 data, file paths, or URLsretrieveMediaFile- Download media as base64getMediaFilesNames- List media files with optional pattern filteringdeleteMediaFile- Remove media files
Model/Template Management
modelNames- List note typesmodelFieldNames- Get fields for a note typemodelStyling- Get CSS styling for a note type
Prerequisites
- Anki with AnkiConnect plugin installed
- Node.js 20+
Installation
This server works in two modes:
- Local mode (STDIO) - For Claude Desktop on your computer (recommended for most users)
- Remote mode (HTTP) - For web-based AI assistants like ChatGPT or Claude.ai
Option 1: MCPB Bundle (Recommended - Local Mode)
The easiest way to install this MCP server for Claude Desktop:
- Download the latest
.mcpbbundle from the Releases page - In Claude Desktop, install the extension:
- Method 1: Go to Settings β Extensions, then drag and drop the
.mcpbfile - Method 2: Go to Settings β Developer β Extensions β Install Extension, then select the
.mcpbfile
- Method 1: Go to Settings β Extensions, then drag and drop the
- Configure AnkiConnect URL if needed (defaults to
http://localhost:8765) - Restart Claude Desktop
That's it! The bundle includes everything needed to run the server locally.
Option 2: NPM Package with STDIO (For Other MCP Clients)
Want to use Anki with MCP clients like Cursor IDE, Cline, or Zed Editor? Use the npm package with the --stdio flag:
Supported Clients:
- 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
Configuration - Choose one method:
Method 1: Using npx (recommended - no installation needed)
{
"mcpServers": {
"anki-mcp": {
"command": "npx",
"args": ["-y", "anki-mcp-http", "--stdio"],
"env": {
"ANKI_CONNECT_URL": "http://localhost:8765"
}
}
}
}
Method 2: Using global installation
First, install globally:
npm install -g anki-mcp-http
Then configure:
{
"mcpServers": {
"anki-mcp": {
"command": "anki-mcp-http",
"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.
Option 3: HTTP Mode (For Remote AI Assistants)
Want to use Anki with ChatGPT or Claude.ai in your browser? This mode lets you connect web-based AI tools to your local Anki.
How it works (simple explanation):
- You run a small server on your computer (where Anki is installed)
- Use the built-in
--ngrokflag to automatically create a public tunnel URL - Share that URL with ChatGPT or Claude.ai
- Now the AI can talk to your Anki through the internet!
New in v0.8.0: Integrated ngrok support with the --ngrok flag - no need to run ngrok separately!
Setup - Choose one method:
Method 1: Using npx (recommended - no installation needed)
# Quick start
npx anki-mcp-http
# With ngrok tunnel (recommended for web-based AI)
npx anki-mcp-http --ngrok
# With custom options
npx anki-mcp-http --port 8080 --host 0.0.0.0
npx anki-mcp-http --anki-connect http://localhost:8765
Method 2: Using global installation
# Install once
npm install -g anki-mcp-http
# Run the server
anki-mcp-http
# With ngrok tunnel (recommended for web-based AI)
anki-mcp-http --ngrok
# With custom options
anki-mcp-http --port 8080 --host 0.0.0.0
anki-mcp-http --anki-connect http://localhost:8765
Method 3: Install from source (for development)
npm install
npm run build
npm run start:prod:http
CLI Options:
anki-mcp-http [options]
Options:
--stdio Run in STDIO mode (for MCP clients)
-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)
--help Show help message
Usage with npx (no installation needed):
npx anki-mcp-http # HTTP mode
npx anki-mcp-http --port 8080 # Custom port
npx anki-mcp-http --stdio # STDIO mode
npx anki-mcp-http --ngrok # HTTP mode with ngrok tunnel
Usage with global installation:
npm install -g anki-mcp-http # Install once
anki-mcp-http # HTTP mode
anki-mcp-http --port 8080 # Custom port
anki-mcp-http --stdio # STDIO mode
anki-mcp-http --ngrok # HTTP mode with ngrok tunnel
Using with ngrok:
Method 1: Integrated (Recommended - One Command)
# One-time setup (if you haven't already):
npm install -g ngrok
ngrok config add-authtoken <your-token> # Get token from https://dashboard.ngrok.com
# Start server with ngrok tunnel in one command:
anki-mcp-http --ngrok
# The tunnel URL will be displayed in the startup banner
# Example output:
# π Ngrok tunnel: https://abc123.ngrok-free.app
Method 2: Manual (Two Terminals)
# Terminal 1: Start the server
anki-mcp-http
# Terminal 2: Create tunnel
ngrok http 3000
# Copy the ngrok URL (looks like: https://abc123.ngrok-free.app)
# Share this URL with your AI assistant
Benefits of --ngrok flag:
- β One command instead of two terminals
- β Automatic cleanup when you press Ctrl+C
- β URL displayed directly in the startup banner
- β
Works with custom ports:
anki-mcp-http --port 8080 --ngrok
Security note: Anyone with your ngrok URL can access your Anki, so keep that URL private!
Option 4: Manual Installation from Source (Local Mode)
For development or advanced usage:
npm install
npm run build
Connect to Claude Desktop (Local Mode)
You can configure the server in Claude Desktop by either:
- Going to: Settings β Developer β 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-desktop/dist/main-stdio.js"],
"env": {
"ANKI_CONNECT_URL": "http://localhost:8765"
}
}
}
}
Replace /path/to/anki-mcp-desktop 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)
| Variable | Description | Default |
|---|---|---|
ANKI_CONNECT_URL | AnkiConnect URL | http://localhost:8765 |
ANKI_CONNECT_API_VERSION | API version | 6 |
ANKI_CONNECT_API_KEY | API key if configured in AnkiConnect | - |
ANKI_CONNECT_TIMEOUT | Request timeout in ms | 5000 |
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>ΒΏCΓ³mo estΓ‘s?</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
notesInfotool returns CSS styling information for proper rendering awareness - The
updateNoteFieldstool supports HTML content in fields and preserves CSS styling - Each note model has its own CSS styling - use
modelStylingto get model-specific CSS
Update Warning
β οΈ 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.
Deletion Safety
The deleteNotes tool requires explicit confirmation (confirmDeletion: true) to prevent accidental deletions. Deleting a note removes ALL associated cards permanently.
Development
Transport Modes
This server supports two 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:stdioornode 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:httpornode dist/main-http.js - Default port: 3000 (configurable via
PORTenv var) - Default host:
127.0.0.1(configurable viaHOSTenv var) - MCP endpoint:
http://127.0.0.1:3000/(root path)
Building
npm run build # Builds once, creates dist/ with both entry points
Both main-stdio.js and main-http.js are in 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:
- Sync version from
package.jsontomanifest.json - Remove old
.mcpbfiles - Build the TypeScript project
- Package
dist/andnode_modules/into an.mcpbfile
The output file will be named based on the current version (e.g., anki-mcp-http-0.5.0.mcpb) and can be distributed for one-click installation.
What Gets Bundled
The MCPB package includes:
- Compiled JavaScript (
dist/directory - includes both entry points) - All dependencies (
node_modules/) - Package metadata (
package.json) - Manifest configuration (
manifest.json- configured to usemain-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 β MCP-specific log
- Server internal logging (pino) β 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
- Go to Run β Edit Configurations
- Add a new Attach to Node.js/Chrome configuration
- Set the port to
9229 - Click Debug to attach
VS Code
- Open the Debug panel (Ctrl+Shift+D / Cmd+Shift+D)
- Select Debug MCP Server (Attach) configuration
- 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",
"/Users/anatoly/Developer/git/anki-mcp-organization/anki-mcp-desktop/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
- Go to Run β Edit Configurations
- Click the + button and select Attach to Node.js/Chrome
- Configure:
- Name:
Attach to Anki MCP (Claude Desktop) - Host:
localhost - Port:
9229 - Attach to:
Node.js < 8orChrome or Node.js > 6.3(depending on WebStorm version)
- Name:
- Click OK
- Click Debug (Shift+F9) to attach
VS Code
- 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"]
}
]
}
- Open the Debug panel (Ctrl+Shift+D / Cmd+Shift+D)
- Select Attach to Anki MCP (Claude Desktop)
- 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 anki-mcp-http-*.tgz
# 2. Install globally from local package
npm run install:local # Installs from ./anki-mcp-http-*.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 packcreates a.tgzfile identical to what npm publish would create- Installing from
.tgzsimulates what users get fromnpm 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: 0.8.0 - Active beta development. New features include integrated ngrok tunneling (--ngrok flag), the twenty_rules prompt for evidence-based flashcard creation, media file management, and improved prompt system. APIs may change based on feedback and testing.
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 (anki-mcp-desktop) 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.
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