"Step-by-step guide to breaking down a request into parts" matching MCP servers:

Enables users to compute symbolic derivatives and integrals, including definite and improper cases, and verify antiderivatives through SymPy-backed MCP tools.

Enables beginners to explore GitHub repositories and issues, assess issue suitability based on their skills and experience, and generate step-by-step contribution roadmaps through an MCP-compatible AI assistant.

This server enables aspiring Google Summer of Code contributors to discover and evaluate mentoring organizations and repositories, find available beginner issues, check claimability, get personalized recommendations, prepare proposals, and track progress using grounded GSoC and GitHub data. It also surfaces official program guidance, anti-spam rules, and GitHub API rate-limit status.

An MCP server that transforms books into agent-callable skill packages, enabling AI agents to use books as guides for evidence, procedures, and tutoring.

Guides users to official WCAG and W3C resources for learning web accessibility, without providing its own explanations.

Enables AI assistants to plan and track McDonald's visits by locating stores, estimating commute calories, recommending nutrition-targeted menu combinations, monitoring orders, running spaced-repetition vocabulary practice during waits, and recording progress in a local dashboard.

Enables AI educators to provide simple explanations, interactive demonstrations, and relatable analogies for complex AI concepts during workshops. Makes artificial intelligence topics accessible and engaging for participants through structured teaching tools.

Provides access to API Ninjas Random Word API to generate random words by type (noun, verb, adjective, adverb) for creative writing, games, and language learning applications.

A local MCP server for Canvas LMS that enables querying courses, assignments, grades, modules, and more from any MCP-compatible AI client.

Helps AI agents answer XCS221 course logistics questions (e.g., deadlines, pacing, repositories) from static in-repo data without external APIs.

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

Enables LLM clients to perform arithmetic and advanced calculations through MCP tools, access math constants and session calculation history, and receive step-by-step guidance for solving equations.

Enables querying of a locally pinned snapshot of the Education-to-Workforce Indicator Framework — 99 indicators and 11.8M observations — to browse questions, describe metrics, resolve places, and fetch or rank data across national, state, county, and district levels.

Enables MCP clients to teach on a view-only local browser chalkboard by drawing equations, plots, molecules, diagrams, and science illustrations step by step, with snapshots and saved lessons.

Enables users to practice graded AI Engineer and Investment Banking interview questions through tools for listing topics, retrieving questions and model answers, getting step-by-step answer frameworks and scoring rubrics, running randomized mock drills, and searching questions offline over stdio.

An MCP toolkit for algorithm learning that enables AI agents to search problems, generate step-by-step hints, analyze code, and create review templates for Baekjoon and Programmers problems.

Connects AI agents to over 2,700 interactive precision scientific, engineering, horological, and bullion calculators, returning verified formulas and step-by-step mathematical proofs without login or API keys.

A step-by-step workshop for building an MCP server that provides weather tools to AI agents, enabling secure API key usage.

Provides access to step-by-step drawing tutorials from easydrawingguides.com, enabling users to search for drawing guides, retrieve detailed tutorial content in Markdown format, and browse categories for artists of all skill levels.

Hand-drawn, interactive diagrams inside the chat: Claude describes what to draw, Sketchy lays it out and renders it, with step-by-step walkthroughs, code architecture, Arduino wiring and locally labeled photos.

Enables AI assistants to search a catalog of origami and paper-craft models, explain the paper and difficulty each one needs, and guide users through illustrated folding steps or suggest projects by occasion, age, difficulty, or time budget. It also exposes craft categories and subject counts, and renders an interactive catalog and step viewer in hosts that support MCP Apps.

Enables retrieving daily hard truths, including today's truth, a random truth, or all 30 day titles, with each truth including a lesson and action step.

A beginner-friendly repository for learning the Model Context Protocol (MCP) using FastMCP and uv, providing step-by-step setup and development workflow.

Enables Alexa+ to coach students through algebra homework by verifying each step with a computer algebra system, providing hints and feedback without revealing answers.

A learning MCP server that transforms technical topics into four structured parts: definition, analogy, example, and hands-on try-it exercises, enabling beginner-friendly study directly from any MCP client.

An MCP server that generates Excalidraw diagrams to visualize algorithm execution step-by-step, supporting multiple data structures and integration with AI assistants.

Enables Alexa+ to coach adults with cognitive disabilities through daily routines by holding state, applying fading rules, and supplying exact prompts that gradually reduce as each step is learned. It also restores support when a step becomes harder and provides auditable reasons for every change.

An MCP server and CLI for step-by-step learning, enabling humans and agents to learn subjects like language tutoring through a structured prompt system.

Enables querying a city road graph for shortest routes by total distance and a 25-room maze for fewest-door paths, returning step-by-step trace explanations and animating each search in a live web viewer.

Enables users to choose among seven decision-making frameworks and work through them step by step with their own situation, ending with one clear decision and a next action. It also chains multiple frameworks for larger decisions and provides model guides and recommendations.