"Using AI to control and access data from Home Assistant and smart home devices" matching MCP servers:

Enables MCP-compatible clients to generate simple study plans from a subject, level, and available minutes, and to produce beginner-level practice questions, all locally without an API key.

Turns Canvas LMS into a scriptable pipeline and exposes it to AI assistants via MCP for querying courses, grades, assignments, and syncing files using natural language.

Enables discovery, retrieval, summarization, comparison, methodology and limitation analysis, research gap identification, and local management of academic papers via arXiv and Gemini AI.

Enables users to check whether a chosen university subscribes to a given journal or paper — via search, DOI, journal title, database, and journal-package queries — returning library holdings plus clickable links the user opens themselves. It supports multiple schools through a picker panel and only ever inspects holdings, never downloading full text.

A fully working MCP server built from scratch in plain Node.js, implementing tools, resources, prompts, notifications, and sampling according to the MCP specification, designed to connect to Claude Desktop or any MCP client.

Enables MCP clients to look up companies, retrieve SEC filings and annual financial facts, compute metrics, create learning cards and quizzes, explain concepts, and track shared family learning profiles using real SEC EDGAR data for educational use.

Enables Claude and ChatGPT to share a single study-progress database for interview prep, coursework, and spaced repetition, with per-user data isolation and server-side SM-2 scheduling for due reviews and study plans.

MCP server that integrates GitHub, Brightspace, Outlook, and local files, enabling natural language queries for assignments, grades, emails, calendar events, repositories, and file operations.

Enables the AI Learning Assistant to perform web searches for current or external information, returning ranked public-web results with titles, URLs, snippets, and scores over Streamable HTTP.

Converts syllabus documents into a searchable study knowledge base. Provides MCP tools to list available syllabi and retrieve structured summaries and extracted text.

Provides educational tools for developers to learn programming concepts, review code, get best practices, compare approaches, generate learning paths, debug, explain code, and quiz themselves.

Enables AI assistants to calculate CGPA, view assignment deadlines, filter deadlines by subject, and search local subject notes.

Combines YouTube subtitle extraction, Wikipedia concept lookup, and arXiv paper search into one pipeline without any API keys, enabling generation of comprehensive study notes from a single YouTube URL.

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 natural-language queries about US K-12 public schools, districts, per-pupil funding and spending, and child poverty estimates from keyless federal data.

This MCP server integrates GitHub issues, academic deadlines (LMS), and a personal task tracker to help AI assistants answer questions like 'What should I work on today?' with a prioritized overview.

Enables local-first personal growth execution where an AI agent maintains the plan and daily tasks, while the user retains control of goals and final decisions.

A set of tools enabling AI agents to interact with Canvas LMS, allowing users to find relevant resources, get course information, and navigate modules through natural language queries.

A spaced-repetition study scheduler that syncs with Obsidian notes and uses SBB commute data to optimize study slots.

Provides a privacy-first adaptive review engine with local SQLite storage, enabling item creation, due review retrieval, grading, and statistics via MCP tools.