"Learning Programming" matching MCP servers:

Provides 23 modular tools for competitive programming, including problem analysis, algorithm planning, code generation, verification, testing, code review, and learning assistance.

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.

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

Provides linear programming (LP), mixed-integer programming (MIP), and quadratic programming (QP) optimization capabilities using the HiGHS solver, enabling AI assistants to solve complex optimization problems like production planning, logistics, and portfolio optimization.

Enables AI assistants to run code in 24 programming languages on HackerEarth's sandboxed servers and read the printed output or errors, without installing local toolchains. It also lists supported languages with exact identifiers for use when submitting code.

Provides AI-powered educational tools for teachers including lesson planning, quiz creation, student progress analysis, learning path recommendations, and rubric generation. Enables educators to automate administrative tasks and personalize learning experiences through natural language interactions.

Read-only FastMCP server providing machine learning stock selection scores, Alpha158 signals, and SHA-256 checksums from Qlib.

Contract-first programming language with a local MCP server for checking types, effects, capabilities, and contracts in agent-written modules. Its review tool compares before and after source sets and returns receipts for new authority, weaker promise tiers, and new Guarded runtime obligations.

An enhanced sequential thinking tool optimized for programming tasks that helps break down complex coding problems into structured, self-auditing thought steps with branching and revision capabilities.

Provides read-only access to StudyLife data including courses, notes, sessions, and learning goals, enabling MCP clients to query study information via natural language.

Recommends study designs for a research question, states the identifying assumptions to verify, and returns runnable R, Python, or Julia code with a formatted citation for every source, drawn from methodological textbooks, an R package, and research articles on causal inference, econometrics, statistics, and machine learning.

A Model Context Protocol server that provides integration with LeetCode APIs, enabling automated interaction with programming problems, contests, solutions, and user data across both leetcode.com and leetcode.cn platforms.

Self-learning memory for AI coding agents. Observes tool sequences, user preferences, and recurring fixes — auto-promotes high-confidence patterns into behavioral rules. 22 tools, 2 prompts, SQLite-backed, zero config.

Enforces a structured reasoning cycle with mandatory reflection and searchable memory, transforming AI agents into deliberate, learning-based thinkers.

Hebbian learning MCP server with neural memory graphs, eligibility traces, and three-factor reward signals. Associative memory that strengthens through use.

Provides OpenCode with adaptive long-term memory by storing preferences, lessons, and usage history locally in SQLite, enabling AI to remember and adapt to users through context-based learning.

Marketing, Search, AI & Machine Learning (Dockerfile is present)

The toolchain of Renyi, a programming language for AI agents: check, format, run and test programs, and read the project map with every function's effects, semantic diffs and chunks for retrieval. One binary, renyi mcp.

Enables AI assistants and developers to analyze code for language-specific best practices and idiomatic patterns across programming languages, CI automation, and configuration formats.

Trainzilla MCP connects Claude to your Trainzilla coach account, turning your client roster, programming, and habit tracking into something you can manage conversationally. Built for fitness coaches running their practice on Trainzilla, it lets Claude pull up client profiles and metrics, build and review workout and diet plans, create and assign habits, run quick calculations (TDEE, macros, 1RM),