"Microsoft Learn - Microsoft's online learning platform for technical skills and certifications" matching MCP servers:

An agent-native teaching OS that gives AI assistants a persistent classroom with courses, lessons, flashcards, and graded exercises via MCP tools.

Enables developers to record feature-based development processes and turn Git changes, AI conversations, token usage, technical decisions, and debugging attempts into structured Obsidian learning reviews.

An MCP server that enforces a pedagogical workflow to teach topics step by step, using research, decomposition, and spaced retrieval practice.

A local MCP server that helps you maintain a personal Japanese learning knowledge base, including vocabulary, confusion relations, mistakes, and spaced-repetition reviews. It provides tools and prompts for managing and reviewing your Japanese learning data without calling external LLM APIs.

A sovereign, AI-driven pedagogical and spaced-repetition skills development MCP server supporting progressive syllabi, Bloom's Taxonomy, and secure LMS handshakes.

Enables AI agents to index, search, and validate lessons learned across project repositories via a local SQLite index, providing learning-loop resources and verified-solution tracking without loading full files into conversations.

Enables AI agents to learn from their work by recording tasks, extracting patterns, detecting mistakes, and proactively surfacing insights, all using the agent's own model through a cooperative intelligence pattern.

Extends the official Obsidian MCP server with intelligent learning and second-brain features, including AI-generated challenges, progress analytics, spaced repetition, and knowledge gap analysis.

This MCP server provides an AI-driven learning and knowledge management platform that automatically summarizes conversations, manages knowledge graphs, tracks project progress, explores new technologies, and generates study plans through specialized agents.

A self-hostable, open-source, semantically-searchable Agent Skills registry delivered over MCP, with a three-tier progressive disclosure architecture.

MCP server implementing progressive disclosure for skill instructions, loading skills on-demand for token efficiency.

Bridges Hermes Agent to the Hermes Intelligence Platform API, enabling tools to read/write learning loop data (context, feedback, signals, memory, etc.) via stdio.

MCP server that unifies and synchronizes AI coding skills across multiple tools, exposing skill discovery and retrieval via list_skills and read_skill.

Enables MCP clients to infer and resolve skills from text, normalize skill names, perform semantic taxonomy searches, and inspect lifecycle governance.

MCP server that provides access to over 100 development skills for frontend, backend, integration, design, devops, and process categories via Claude Code and other MCP clients.

Connects AI assistants to Hudu IT documentation platform with 43 tools, Markdown output, and multi-tenant support for MSPs.

Implements cognitive science-backed interleaved learning techniques to create study plans, generate mixed-topic quizzes, manage flashcard decks, and track learning progress for optimal knowledge retention.

Provides stateful prompt optimization using research-backed techniques like APE and OPRO, learning from historical performance data via a vector database. It enables users to automatically refine prompts, retrieve high-performing examples, and track performance analytics through iterative feedback.

Manages a Neo4j knowledge graph of reusable Python functions, documentation, and environment variables, enabling dynamic script composition and execution with automatic dependency management and secret protection.

Educational MCP server with 17 tools for mathematical calculations, matrix operations, statistical analysis, and data visualization. Includes persistent workspace, cloud hosting, and safety features like restricted eval.