by zlatanpham
Anki MCP Server: use AI to manage Anki decks, create basic & cloze cards, add cards and handle review queues via natural
Connects LLMs to Anki flashcard software, allowing you to create, search, and manage flashcards and decks through AnkiConnect.
Anki MCP Server is a community-built MCP server published by zlatanpham that provides AI assistants with tools and capabilities via the Model Context Protocol. Anki MCP Server: use AI to manage Anki decks, create basic & cloze cards, add cards and handle review queues via natural It is categorized under productivity, developer tools.
You can install Anki MCP Server in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.
MIT
Anki MCP Server is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.
Add new capabilities to Claude beyond text generation
Example
Access external data sources, execute code, interact with tools and services
Transform Claude from chatbot to action-taking agent
Provide Claude with access to relevant context and data
Example
Load project documentation, access knowledge bases, query databases
Get more accurate, context-aware responses
Automate multi-step workflows combining AI and external tools
Example
Research → Summarize → Create document → Send notification
Complete complex tasks end-to-end without manual steps
Share your MCP server with the developer community
I recommend Anki MCP Server for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
Anki MCP Server is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
According to our notes, Anki MCP Server benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
Anki MCP Server is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
Strong directory entry: Anki MCP Server surfaces stars and publisher context so we could sanity-check maintenance before adopting.
We wired Anki MCP Server into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
Anki MCP Server is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
Anki MCP Server has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
Strong directory entry: Anki MCP Server surfaces stars and publisher context so we could sanity-check maintenance before adopting.
We evaluated Anki MCP Server against two servers with overlapping tools; this profile had the clearer scope statement.
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An MCP (Model Context Protocol) server that provides tools for interacting with the Anki API. This server allows AI assistants to manage Anki decks and cards through simple tool calls.
npm install -g @x-mcp/anki
# or
pnpm add -g @x-mcp/anki
# Install dependencies
pnpm install
# Build the project
pnpm run build
# Run in development mode (auto-restart on changes)
pnpm run dev
# Run the server
pnpm start
# Lint and format code
pnpm run lint
pnpm run format
Add this to your MCP client settings:
{
"mcpServers": {
"anki-mcp": {
"command": "npx",
"args": ["-y", "@x-mcp/anki@latest"],
"env": {
"ANKI_BASE_URL": "http://localhost:3000", // Anki API base URL
"ANKI_API_KEY": "ank_YOUR_API_KEY_HERE" // Your Anki API key
}
}
}
}
Create a .env file:
# Required: Anki API configuration
ANKI_BASE_URL=http://localhost:3000/api/v1
ANKI_API_KEY=ank_YOUR_API_KEY_HERE
# Optional: External tools API configuration
API_URL=https://your-api-endpoint.com/tools
API_KEY=your-api-key
Once configured, the AI assistant can use commands like:
Each tool makes direct HTTP requests to the Anki API and returns the response data.
The tools interact with an Anki API that should have the following endpoints:
GET /api/v1/decks - List decksPOST /api/v1/decks - Create deckPOST /api/v1/decks/{deckId}/cards/batch - Add cardsGET /api/v1/study/queue - Get review queueMIT
Prerequisites
Time Estimate
15-60 minutes depending on server complexity
Steps
Troubleshooting
✓ Do
✗ Don't
💡 Pro Tips
Architecture
Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.
Protocols
Compatibility
✓ Use when
Use when you need Claude to access external data, execute actions, or integrate with tools. Best for extending AI capabilities beyond conversation.
✗ Avoid when
Avoid when native integrations exist (use official APIs directly), for real-time critical systems, or when security/compliance requires zero external dependencies.