"Using an MCP server to generate structured ADK agents" matching MCP servers:

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 the generation of educational content such as multiple choice questions, lesson plans, and flashcards by connecting local Ollama models to Claude. It leverages the Educhain library to provide structured AI-powered learning tools through the Model Context Protocol.

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 LLMs to search and retrieve exam problems, solutions, and answers from the СДАМ ГИА educational platform across multiple subjects. It supports fuzzy text matching, catalog browsing, and structured data retrieval to assist with academic study and test preparation.

Provides tools for managing student knowledge graphs, enabling structured representation of courses, assignments, exams, concepts, and study resources.

An educational MCP server example demonstrating how to build a server that integrates with LLM clients like Claude Desktop.

Enables querying Schoox LMS data (users, courses, enrollments, etc.) via natural language using AI assistants, without writing API code.

Rabbithole provides an infinite canvas for learning by allowing users to open documents, select text, ask questions, and receive answers that open as child documents, all running locally via an MCP server.

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

Enables searching Brown University courses, getting detailed course info, and checking schedule conflicts via natural language, using the university's public course catalog API.

Helps independent inventors calculate USPTO fees, determine entity status, track patent deadlines, and understand procedural rules without needing an attorney.

Provides a comprehensive creative thinking tool with methods like structured process, perspective shift, and constraint-based innovation to enhance divergent thinking.

Enables searching and retrieving course listings, departments, and syllabi from National Chengchi University's public course API using natural language.

Calculates Korean traditional Dangsaju 12 stars based on birth date and time, returning deterministic structured data with star attributes and period readings.

Calculates Pythagorean numerology core numbers (Life Path, Expression, Soul Urge, etc.) from name and birth date, returning structured text and a summary card PNG.

Calculates pizza dough ingredient quantities using baker's percentages from ball count, weight, hydration, flour blend, and fermentation schedule. Returns grams of each flour, water, salt, and yeast with a readable summary and structured JSON.

Enables AI agents to search and retrieve opportunities from the Opportunities Circle catalog, including scholarships, fellowships, internships, grants, jobs, and more. Supports filtering by type, country, funding, and tags, with full details and official apply links.

A minimal Model Context Protocol server built with the official Python SDK. It exposes one tool, define, which looks up the definition of an English word using the free dictionaryapi.dev API.

Enables browsing situation groups and reading full-text chapters from a curated library of 403 deep reads, with the model matching situations to entries instead of using keyword search.

Provides AI agents structured access to the Gospel Library — scriptures, General Conference talks, handbooks, manuals, and magazines — with local semantic search.