Ankify

Create Anki decks with text-to-speech audio from arbitrary input using LLM and TTS services.

Features

• MCP Server: Use with any MCP-compatible AI client, locally or in the cloud. No need for any API keys
• CLI: Standalone command-line tool, uses LLM through openai-compatible API
• Multi-language TTS: Azure, AWS Polly, and free Edge TTS support
• Customizable prompts: Curated vocabulary creation prompt templates for any language pair and note type with few-shot examples and custom instructions
• Packed to Anki: The resulting .apkg file is to be opened in Anki.

If the deck name in settings is equal to the name of an existing deck in your Anki, it will be loaded directly into the existing deck. Clarification of possible notes types: see docs/Anki_note_types.md.

Installation

Local MCP Server

For local MCP server with free Edge TTS:

pip install ankify[local-mcp]

Full Local (CLI + All TTS)

For all the features including CLI and all TTS providers:

pip install ankify[local-all]

FastMCP Cloud

You need this only when deploying to FastMCP Cloud. This is the default installation option just because that's how it works with FastMCP Cloud. So most probably you don't need it.

pip install ankify

Development

git clone https://github.com/AlexanderKazakov/ankify.git
cd ankify
uv venv --python 3.12
uv pip install -e .[local-all,dev]

MCP Server

Ankify provides an MCP server for integration with LLM clients

Cloud Deployment (FastMCP)

Deploy to FastMCP Cloud for hosted MCP access. The server uses Azure TTS by default.

Local MCP Server

Add to your MCP client configuration:

{
  "mcpServers": {
    "ankify": {
      "command": "uv",
      "args": [
        "--directory",
        "/path/to/ankify",
        "run",
        "python",
        "-m",
        "ankify.mcp.ankify_mcp_server"
      ]
    }
  }
}

MCP Tools & Prompts

Prompts:

• vocab - Create vocabulary table (universal template for any language pair, note type, custom instructions)
• vocab_en_ru_fo - shortcut for English-Russian, forward-only not
• vocab_ge_en_fb - shortcut for German-English, forward-and-backward
• deck / deck_fo / deck_fb - Create Anki deck from vocabulary table (instructs AI to use the conversion tool properly)

Tools:

• convert_TSV_to_Anki_deck - Convert TSV vocabulary to .apkg file

TTS Providers

Provider	Package	Cost	Notes
Azure	azure-cognitiveservices-speech	Paid (free tier)	The broadest language support. Good quality. "Neural" engines only.
AWS Polly	boto3	Paid (free tier)	Good quality for "Neural" engine. Worse for languages with "Standard" engine only.
Edge	edge-tts	Free	Good quality, same to Azure. May rate-limit, but usually enough for local usage.

From my (limited to English, German, and Russian) experience, all "Neural" engines create good enough pronunciation in 99.9% cases and good for learning. "Standard" engines are a bit worse and OK for native speakers to understand, but not good enough to learn a foreign language pronunciation. But "Standard" engines are only on AWS, so it's quite unlikely you'll use them anyway, while all the default options use providers with "Neural" engines.

Install specific providers:

pip install ankify[tts-azure]
pip install ankify[tts-aws]
pip install ankify[tts-edge]

CLI

For CLI usage documentation, see docs/CLI.md.

Environment Variables

Provider credentials can be set via environment variables or .env file, see .env.example for examples.

License

MIT