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Optimize spaced-repetition study sessions using Obsidian notes and commute data.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "learning-assistant-mcp" yet — see the docs or source repo.
Using the review cadence from my 'Machine Learning' folder in Obsidian and my SBB commute times for this week, create a 7-day spaced-repetition study plan with suitable review slots and matching notes for each day.
A day-by-day study plan with recommended review slots, linked notes, and review priorities.
Analyze my SBB travel schedule for tomorrow, identify 10- to 25-minute gaps, and select the most suitable cards or notes from Obsidian for those review windows.
A set of time-matched review suggestions that help me use commute gaps efficiently.
I have a backlog of overdue reviews. Using the due review items in Obsidian and my SBB commute schedule for the next three days, redistribute the study tasks to avoid overloading any single day.
A rebalanced review schedule explaining the daily assignments and workload distribution.
Extract, filter, and query Obsidian tasks and metadata from Markdown files.
Manage Obsidian tasks with CRUD, queries, and date-based filtering.
Enable AI to manage research memory in Obsidian across sessions.
Manage student progress, analyze assessments, and identify learning gaps and priorities.
Helps developers learn coding concepts, review code, and build learning paths.
Connect Obsidian vaults for local-first AI memory search and knowledge management.