"A system for managing schedules or emails (MCP)" matching MCP servers:

A Model Context Protocol server that exposes an airline design system as a queryable knowledge base, enabling AI to discover components, find components for use cases, and scaffold prototypes.

Automated MCP server for the Insider Design System. Enables AI assistants to discover, understand, and generate code for over 60 Design System components with automated extraction from source code.

Creates a local MCP runtime for design-system repositories, enabling AI coding agents to look up and use real components, icons, and tokens instead of guessing.

Enables AI coding agents to discover, compare, select, and enforce design systems and component libraries, with installation guidance, component APIs, and strict adherence directives to prevent default substitutions.

Enables Large Language Models to access and manipulate Autodesk Revit models through a pyRevit-based bridge and the Model Context Protocol.

A Model Context Protocol server that exposes a versioned brand package (tokens, rules, recipes, media rights, and audit gates) as resources, tools, and prompts for AI agents. It enables agents to plan and audit on-brand UI, image, motion, and video outputs while remaining read-only and credential-free.

Connects MCP-compatible AI assistants to Azgaar's Fantasy Map Generator so they can view, inspect, edit, and export fantasy maps in a live local browser, including borders, states, terrain, layers, and files. It runs locally and offline after installation, supports collaborative manual editing, undo, autosave, and text-only map output for models that cannot see images.

Provides AI agents with component documentation, usage examples, and design tokens from the WordPress Design System, enabling them to follow the latest design system guidance for creating user interfaces.

Enables coding agents to query a workspace's design system before writing UI and validate generated code against the same system afterward, using configurable token and component sources.

Gives LLM agents spatial awareness inside Autodesk Maya, enabling scene inspection and measurement, aesthetic and engineering audits, camera planning, checkpoint/rollback safety, asset import, and viewport or render previews. Agents can also execute arbitrary Python in Maya to build and verify 3D scenes against engineering rules instead of writing blind.

Enables AI-driven 3D modeling and scene creation in Blender, allowing LLMs to create, modify, and manipulate objects, materials, and assets through natural language.

Enables controlling CLO3D from any MCP client to inspect projects, create and edit patterns, manage fabrics and colorways, run simulations, and export models through chat.

A local, offline MCP server that enables AI agents to collaborate with SketchUp for controlled modeling, editing, and review tasks via 41 MCP tools.

Local MCP bridge that exposes the ChatGPT Figma connector to OpenCode without launching Codex, using the existing authenticated session.

Enables AI agents to query a design system's components, tokens, icons, patterns, and usage or accessibility guidelines through standardized MCP tools, with pluggable adapters for different data sources.

Translates natural language commands into structured geometric operations for a simulated CAD engine using LLMs. It enables users to create shapes, modify dimensions, and perform 3D operations like extrusion through the Model Context Protocol.

Enables LLMs to drive Blender through socket-based two-way communication, letting them create and modify 3D objects, apply materials, run Blender Python, and fetch or generate assets while visually verifying results. Supports prompt-assisted 3D modeling, scene creation, and manipulation.

Enables coding agents to read ground truth about a React design system — components, props, cva variants, tokens and docs — over MCP so they write UI that matches it. It also exposes a check_ui linter agents run on their own output, returning rule ids, locations and concrete fixes before review.

Enables Claude to draw, verify, correct, and organize precise 2D architectural geometry directly in an open Vectorworks file, including exact arcs, measurements, classes, layers, and self-checking fixes.

Enables AI assistants to inspect and organize Adobe Premiere Pro projects, edit timelines with frame-accurate cuts and trims, animate motion and opacity keyframes, and trigger exports through natural language.

Provides AI assistants with access to WordPress Design System component information and design guidance.

Enables AI assistants to programmatically inspect projects, create compositions and layers, apply effects, animate properties, and manage render jobs in Adobe After Effects through natural language.

Enables AI coding agents to read and write a user's Figma file through the Figma Plugin API, offline and privately, without API tokens or rate limits.

Enables Claude and other MCP clients to create and modify SOLIDWORKS parts, assemblies, sheet metal, weldments, drawings, and bills of materials from natural-language requests, run strength simulations, and receive model views and stress maps as images.

UAE Design System (AEGOV DLS) for AI assistants: component catalogue, design tokens, UAE PASS & Emirates ID scaffolds, snippet validation.

Self-hosted MCP server that enables ChatGPT agents to perform health checks, fetch design request context, and submit agent results back to a design system backend.

Provides resources, tools, and prompts for a Design System via MCP protocol, enabling component search, reading, and related component discovery.

The Wellx Design System MCP enables AI agents to access the single source of truth for Wellx design, including tokens, component specs, rules, and search, ensuring consistent design implementation across surfaces.

Connects MCP-aware AI clients to a live SketchUp session so users can create and modify 3D models, apply materials, perform booleans and joinery, and export scenes through natural-language prompts.

MCP server that exposes the @bunge/ds-components design system catalog, allowing AI assistants to list, search, and retrieve component details including inputs, outputs, usage examples, and import instructions.