Notion-Anki MCP Server

A Model Context Protocol (MCP) server that automatically generates Anki flashcards from Notion pages. This tool extracts questions and answers from Notion toggle blocks and converts them into structured Anki cards using OpenAI's API, with real-time import via AnkiConnect.

Use Cases

Students: Convert study notes from Notion into flashcards for spaced repetition
Professionals: Transform training materials and documentation into memorable cards
Educators: Quickly create quiz content from lesson plans
Researchers: Convert paper summaries and key concepts into study materials

Features

Notion Integration: Extracts content from Notion pages via official API
Smart Parsing: Recognizes toggle blocks as question-answer pairs
AI Enhancement: Uses OpenAI to refine and improve flashcard quality
Real-time Import: Automatically adds cards to Anki via AnkiConnect
MCP Protocol: Works with MCP-compatible clients like Claude Desktop

Prerequisites

Before setting up this project, ensure you have:

Notion API Access
- Create a Notion integration
- Get your API key from the integration settings
OpenAI API Access
- Sign up for OpenAI API
- Create an API key with sufficient credits
Anki Setup
- Install Anki desktop application
- Install AnkiConnect add-on
- Keep Anki running during flashcard generation
Python Environment
- Python 3.8 or higher
- pip package manager

Quick Start

1. Clone the Repository

git clone https://github.com/yourusername/notion-anki-mcp.git
cd notion-anki-mcp

2. Install Dependencies

pip install -r requirements.txt

3. Environment Configuration

cp .env.example .env

Edit .env with your API keys:

NOTION_API_KEY=your_notion_api_key_here
OPENAI_API_KEY=your_openai_api_key_here

4. Start the MCP Server

python server.py

How to Structure Your Notion Pages

For the tool to work effectively, structure your Notion pages as follows:

Toggle Block Format

Create toggle blocks where:

Toggle title = Your question
Toggle content = The answer/explanation

Example structure:

📝 Machine Learning Concepts

🔽 What is supervised learning?
   Supervised learning is a type of machine learning where...
   - Uses labeled training data
   - Learns mapping from inputs to outputs
   - Examples: classification, regression

🔽 What's the difference between classification and regression?
   Classification predicts categories/classes while regression predicts continuous values...

Supported Content Types

Within toggle blocks, the tool supports:

Plain text paragraphs
Bulleted lists
Numbered lists
Basic formatting (bold, italic, etc.)

Usage

Via MCP Client (Recommended)

Configure your MCP client to connect to this server
Use the available tools:
- search_page: Find a Notion page by name
- extract_page_content: Extract questions and answers from a page
- generate_flashcards: Create and import Anki cards

Direct Python Usage

import asyncio
from server import search_notion_page, fetch_page_content, generate_flashcards_gpt

async def create_flashcards(page_name):
    # Search for the page
    page_result = await search_notion_page(page_name)
    if not page_result:
        print(f"Page '{page_name}' not found")
        return
    
    # Extract content
    topics, content = await fetch_page_content(page_result['page_id'])
    
    # Generate and import flashcards
    cards = await generate_flashcards_gpt(page_name, topics, content)
    print(f"Created {len(cards)} flashcards for '{page_name}'")

# Run the example
asyncio.run(create_flashcards("Your Page Name"))

API Reference

MCP Tools

`search_page`

Searches for a Notion page by name.

Parameters:

page_name (string): The title of the Notion page to search for

Returns:

{
  "status": "success",
  "page_name": "Page Title",
  "result": {
    "result": "Found",
    "page_id": "page-uuid",
    "link": "https://notion.so/..."
  }
}

`extract_page_content`

Extracts questions and answers from a Notion page.

Parameters:

page_id (string): The UUID of the Notion page

Returns:

{
  "status": "success",
  "topics": ["Topic 1", "Topic 2"],
  "content": {
    "Question 1?": "Answer 1...",
    "Question 2?": "Answer 2..."
  }
}

`generate_flashcards`

Creates Anki flashcards from extracted content.

Parameters:

page_name (string): Name for the Anki deck
topics (array): List of topics/headings from the page
content (object): Question-answer pairs

Returns:

{
  "status": "created",
  "cards": [...],
  "message": "Created flashdeck and cards for 'Page Name' in Anki"
}

Troubleshooting

Common Issues

"Page not found" Error

Ensure the page name matches exactly (case-sensitive)
Verify your Notion integration has access to the page
Check that the page is in a shared workspace

"AnkiConnect not responding" Error

Make sure Anki desktop is running
Verify AnkiConnect add-on is installed and enabled
Check that Anki isn't in review mode or showing a dialog

"OpenAI API Error" Error

Verify your OpenAI API key is correct and active
Check your API usage limits and billing
Ensure you have access to the GPT-4 models

Empty flashcards generated

Check that your Notion page uses the toggle block format
Ensure toggle blocks contain text content
Verify the page has actual content, not just headers

Debug Mode

Enable debug logging by modifying server.py:

import logging
logging.basicConfig(level=logging.DEBUG)

Contributing

Fork the repository
Create a feature branch (git checkout -b feature/amazing-feature)
Commit your changes (git commit -m 'Add amazing feature')
Push to the branch (git push origin feature/amazing-feature)
Open a Pull Request

License

This project is licensed under the MIT License - see the LICENSE file for details.

Acknowledgments

Notion API for excellent documentation
AnkiConnect for Anki integration
Model Context Protocol for the MCP standard
OpenAI for powerful language models

Made with ❤️ for better learning and knowledge retention

This server cannot be installed

security - not tested

license - permissive license

quality - not tested

How are these scores calculated?

hybrid server

The server is able to function both locally and remotely, depending on the configuration or use case.

Automatically generates Anki flashcards from Notion pages by extracting questions and answers from toggle blocks. Uses OpenAI to enhance card quality and imports them directly into Anki via AnkiConnect for spaced repetition learning.

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