Generate a personalized learning path by analyzing a student's subject, current level, learning style, goals, and weekly study hours.
MIT
470,177 tools. Updated 2026-08-22 00:51
"Resources for Learning a Subject" matching MCP tools:
- Create a structured learning path with steps, resources, and milestones by specifying your topic, current level, and target proficiency. Receive a personalized roadmap to guide your study.MIT
- Search and list Microsoft Sentinel tutorials and learning resources by name or file path. Find up to 100 relevant results for security training and reference.MIT
- List learning materials for a student, filterable by semester and subject, showing name, discipline, teacher, and download or external URL.
- Create a structured learning path for a programming library based on your experience level—beginner, intermediate, or advanced—with progressive topics and resources.MIT
- Subscribe to an e-learning course for a collection to access training materials and resources.Functional Source , Version 1.1, MIT Future
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- Retrieve study materials and learning resources for any subject. Filter resources by subject to find relevant content quickly.MIT
- Query structured training programs (learning paths) to retrieve metadata, enrollments, and student lists, with pagination and filters.MIT
- Get the complete overview of the Dataflowr Deep Learning course: all sessions, modules, and their relationships, to provide students with a clear learning path.Apache 2.0
- Search for trusted tools, articles, and resources recommended by domain experts, with explanations of their value.MIT
- Translate bash commands into PowerShell scripts for debugging and learning, without executing them.MIT
- Analyzes image metadata and applies machine learning to determine if an image is AI-generated or human-made.MIT
- Retrieve lecture notes, explanations, and learning objectives for any module. Use this to answer conceptual questions about course topics.Apache 2.0
- Submit the final success or failure, outcome, and proof for a completed action, closing the loop for accountable fleet learning.MIT
- Append a learning entry to a skill's memory to retain insights for future runs. After completing a skill, capture what failed or could be improved, then store it as a concise note tied to that skill.MIT
- Generate zero-shot forecasts for countries with limited data by applying regime-similarity transfer learning. Ideal for countries lacking long event history.MIT
- Approve a Tier 2 learning pattern for promotion to Agent Brain using its pattern ID. Each approval is cryptographically sealed with a ProofLink receipt.MIT
- Delete a learning record using its unique ID. First, use list_learnings to find the correct ID.Business Source 1.1
- Retrieve complete details for a specific learning outcome by its ID, including optional default mastery levels and colors, to support assessment tracking and curriculum planning.MIT
- Log learning entries with validation and duplicate detection. Appends to memory, returns status (added, duplicate, conflict, etc.).AGPL 3.0