Learning Optimizer

Learning Optimizer

A personalised spaced-repetition engine: it models each learner’s forgetting curve per item and schedules the fewest reviews that still hit a target retention. Built on Ebbinghaus, Leitner / SM-2 (Anki’s baseline), Half-Life Regression and FSRS. Also builds a full study plan that peaks retention by exam day.

Registry name	ai.saifs/learning-optimizer
Endpoint	https://learning-optimizer-mcp.saifs.ai/mcp
Transport	Streamable HTTP (remote, nothing to install)
Auth	OAuth 2.1 — PKCE (S256) and dynamic client registration; your client opens a sign-in page on first use
Publisher	SAIFS AI

Install

VS Code / GitHub Copilot

Add to .vscode/mcp.json (workspace) or your user mcp.json:

{
  "servers": {
    "saifs-learning-optimizer": {
      "type": "http",
      "url": "https://learning-optimizer-mcp.saifs.ai/mcp"
    }
  }
}

Then start the server from the MCP view and sign in when prompted.

Claude (claude.ai, Desktop)

Settings → Connectors → Add custom connector, and paste:

https://learning-optimizer-mcp.saifs.ai/mcp

Claude Code

claude mcp add --transport http saifs-learning-optimizer https://learning-optimizer-mcp.saifs.ai/mcp

Any other MCP client

Point it at https://learning-optimizer-mcp.saifs.ai/mcp using the Streamable HTTP transport. The server returns 401 with a WWW-Authenticate: Bearer … resource_metadata=… challenge, so OAuth-aware clients sign in automatically.

Tools

Tool	What it does
schedule_review	Next optimal review time and predicted recall probability for one learner-item after the last result.
due_reviews	Today’s review queue for a learner, priority-ordered.
predict_retention	Probability of recall for an item at a future date.
optimize_study_plan	Full schedule over an item bank so retention peaks on exam day.
forgetting_curve	Fitted decay curve and parameters for one learner-item.
explain_schedule	Why this interval: model, evidence and confidence.

Example prompts

• “This student just missed item 142. When should they review it next, and what’s P(recall) then?”
• “What should this learner review today, in priority order?”
• “Exam is 28 days out. Build a study plan over this item bank so they peak on the day.”

Support

• Website: https://saifs.ai
• Issues: https://github.com/Saify-Technologies/saifs-ai-mcps-docs/issues
• Privacy: https://saifs.ai/privacy_policy