"Comment perdre du poids (How to lose weight)" 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 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.

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

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.

A curriculum that teaches AI agents how to spend their own money. Sixteen lessons from "what is a wallet" to your first x402 purchase. Teacher, not butler — never signs, pays, or holds keys.

Provides pet nutrition tools for AI agents, enabling cup-to-grams conversion, RER/MER calorie calculations, and ideal weight lookup by breed with source URLs.

A beginner-friendly MCP server built in plain Node.js/JavaScript that exposes five tools (calculator, UUID generator, read notes, get weather, password generator) to teach how the Model Context Protocol works under the hood.

A demonstration MCP server for educational purposes, showcasing how to build and integrate MCP servers with LLM clients like Claude Desktop.

MCP server for Canvas LMS, providing 115+ tools to read courses, assignments, submissions, rubrics, quizzes; grade, comment, manage course content, and handle Canvas admin workflows from any AI agent.

A learning-focused MCP server that demonstrates how to build arithmetic tools for AI assistants, currently featuring addition functionality with structured input/output.

A self-hostable, vulnerable-by-design MCP server for learning how object-level authorization bugs (BOLA/IDOR) appear in multi-tenant tools.

Provides an educational overview of MCP architecture, tools, resources, and prompts, and explains how to build, connect, and deploy MCP servers.

Exposes five deterministic tools over stdio so LLM agents can evaluate all seven kill methods, plan complete well kills and CWI stripping/snubbing operations, and create or step live simulator sessions without hallucinating safety-critical pressure math. Returns kill mud weight, MAASP, stage-by-stage procedures, rig gauges, kill sheets, and graded debriefs.

A deliberately tiny, risk-free MCP server for learning how MCP directory listings work. Three tools, no API calls, no user data, no network calls.

A read-only MCP server that lets users find how to type any character on a French keyboard, learn AZERTY from another keyboard layout, compare layouts, and check typing exercises, optionally with a visual keyboard, without accounts or retained data.

Enables clients to calculate second-order dynamics metrics and design early-stage brackets, including mass-spring-damper parameters, step-response metrics, pole and gain design, hand checks, and candidate ranking. Inputs are unit-annotated and schema-validated before execution.

Enables any MCP client to surface twelve structured thinking frameworks for clarifying questions, learning, problem-solving, decision-making, and self-reflection, with fillable slash commands for humans and programmatic retrieval for agents.

Provides read-only access to Canvas LMS data, enabling an LLM to query courses, assignments, grades, submissions, announcements, discussions, modules, pages, and files via the Canvas REST API.

Enables interaction with the Canvas LMS API to manage courses, assignments, submissions, grades, discussions, modules, files, enrollments, and account-level administration for students, instructors, and account admins. Supports both stdio and streamable HTTP transports with robust pagination, retries, and error handling.

Enables AI assistants to look up passages, draw random entries, search teachings by situation or theme, and produce voice-guided readings from books of wisdom such as the Tao Te Ching.

Enables ChatGPT to turn uploaded course materials into interactive quizzes with multiple question types, in-chat answering, automated grading, and results analysis.

Enables AI agents to search and look up the Jisho.org Japanese-English dictionary by English keyword, kanji, kana, or romaji, returning headwords, readings, JLPT levels, common-ness, and grouped English meanings. Useful for translating words, checking how a term is read, or finding Japanese equivalents for an English concept.

MCP server that enables AI assistants to access a user's Canvas LMS data, including courses, assignments, grades, and file extraction, with OAuth and bearer token authentication.

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.

A public-safe demo MCP server for learning how to package Tools, Resources, and Prompts, using fictional contract text and local demo rules only.

An MCP server for Perigee, the open-source 3D viewer of the artificial objects orbiting the Earth, the Moon and Mars and of the spacecraft crossing the solar system. It lets an AI assistant (a teaching assistant, for example) answer questions such as “how far is Mars from the Earth on 1 December 2026?”, “where is the ISS now?” or “what is Lucy's mission?”, and hand the student a live 3D view, with

A comprehensive learning platform for Model Context Protocol development that teaches MCP concepts through hands-on modules including text processing, file operations, and database integration. Designed as an educational tool with progressive difficulty levels from basic to advanced MCP server development.

MCP server that lets Claude look up a student's daily class schedule. It includes a built-in mock timetable and uses Streamable HTTP transport, requiring no API credentials to try.

Enables agents to build and inspect AI-safety reading volumes by mounting live arXiv papers and open-access textbooks, grading how well those volumes cover ten risk classes, and exporting syllabi or sealed JSON. Every mutation is appended to a replayable SHA-384 audit chain that can be verified link by link.

Enables LLM agents to compute shortest paths and all-destination distances on undirected weighted graphs provided as simple text edge lists, returning optimal routes, total costs, and segment details.