# SM2 Spaced Repetition MCP for AI Agents AI Agent Connect > SM2 Spaced Repetition is an Connector that automates the math behind memory retention. It uses the SM-2 algorithm to calculate exactly when you should review a piece of information based on how well you remembered it last time. It handles the heavy lifting of updating easiness factors and scheduling intervals, so your AI agent can manage a massive deck of flashcards or study notes without missing a beat. ## Overview - **Category:** productivity - **Price:** Free - **Endpoint:** https://edge.vinkius.com/vk_preview_aye8K1HCPAsF2EMMPYXQSOjgV2am8CM4RpYUeluy/ai-agent-connect - **Tags:** spaced-repetition, sm2, anki, algorithm, memory, study ## Description Imagine you have a massive amount of information to memorize, like a new language, a medical curriculum, or a complex coding framework. Usually, you'd have to manually track which cards are due and how difficult they feel, which is a chore that often leads to burnout. This Connector changes that by letting your AI agent handle the scheduling logic for you. It follows the same scientifically-backed rules as major flashcard apps to ensure you see the right information at the perfect moment to move it into long-term memory. Instead of just listing notes, your agent can now actively manage a learning system, adjusting the frequency of reviews based on your actual performance. It turns a static list of facts into a dynamic, evolving study plan. By connecting this to the Vinkius catalog, you get a reliable way to keep your knowledge fresh without the manual overhead of tracking every single review. You just tell your agent what you remembered, and it does the math to figure out when you'll need to see it again. ## Prompt Examples **Prompt:** ``` Update my cards with these scores: ID 1: 5, ID 2: 2 ``` **Response:** ``` Card 1 is now scheduled for a longer interval, and Card 2 has been reset to a 1-day interval. ``` **Prompt:** ``` What are the default settings for a new card? ``` **Response:** ``` New cards start with an initial Easiness Factor of 2.5 and an initial interval of 1 day. ``` **Prompt:** ``` Check if these scores are valid: [6, 3, -1] ``` **Response:** ``` The scores 6 and -1 are invalid. All scores must be integers between 0 and 5. ``` ## Capabilities ### Calculate optimal review dates The Connector determines the next date you need to see a fact based on your previous performance. ### Update easiness factors It adjusts how difficult a piece of information is perceived to be over time. ### Process multiple card reviews Your agent can update a whole batch of cards in a single request to save time. ### Reset card intervals The system automatically resets the schedule for cards you failed to remember. ### Check score validity It ensures your performance scores stay within the required range for accurate math. ## Use Cases ### Batch updating study cards A med student tells their agent they got 3/5 on a batch of anatomy cards. The agent uses evaluate_review_batch to push those reviews further out. ### Validating study scores A language learner asks their agent to check if a score of -1 is valid, and the agent corrects the input to stay within the 0-5 range. ### Checking default card settings A developer wants to know the default settings for new cards to ensure their training deck starts with a 1-day interval. ### Corporate knowledge retention A corporate trainer has an agent update 50 employee training cards at once after a monthly knowledge check. ## Benefits - Save hours on manual scheduling by letting the Connector calculate your next review dates automatically. - Improve memory retention by using the same SM-2 algorithm found in top-tier flashcard apps. - Handle bulk updates quickly with evaluate_review_batch to process dozens of cards in a single command. - Keep your study data consistent by letting your agent manage easiness factors based on your performance history. - Reduce cognitive load by removing the need to track when to study what from your daily to-do list. ## How It Works The bottom line is your agent handles the complex math of memory science so you can focus on actually learning the material. 1. Connect your AI client to the SM2 Spaced Repetition MCP via Vinkius. 2. Provide your agent with the scores for the cards you just reviewed. 3. Receive updated review dates and adjusted difficulty levels for your entire deck. ## Frequently Asked Questions **How does the SM2 Spaced Repetition MCP help me learn faster?** It uses the SM-2 algorithm to show you information right before you're about to forget it. This optimizes your study time so you spend less time on easy stuff and more time on the hard parts. **Can I use this Connector with my existing study notes?** Yes, you can have your agent use this to manage the review schedule for any notes or facts you're trying to memorize. **Does the SM2 Spaced Repetition MCP handle bulk updates?** Yes, it can process multiple card reviews at once. This makes it much faster to update large sets of information after a study session. **What happens if I get a card wrong?** The Connector will automatically adjust the easiness factor and shorten the review interval, ensuring you see that specific card again much sooner. **Is this Connector good for learning a new language?** It's perfect for that. It handles the math of vocabulary retention so you can focus on practice and speaking. **How do I know if my scores are valid?** The system requires scores between 0 and 5. Your agent can check these for you to make sure your data stays clean. **How does the SM-2 algorithm work?** It uses review quality scores (0-5) to adjust the interval between reviews and the Easiness Factor, helping to schedule reviews at the peak of your forgetting curve. Tools available: `your_tool_name`. **Can I process multiple cards at once?** Yes, the `evaluate_review_batch` tool allows you to send a batch of card updates in a single request for maximum efficiency. **What are the supported card statuses?** The system manages cards through three stages: New, Learning, and Mature.