"Multi-agent AI systems for collaborative code development" matching MCP servers:

Enables AI coding assistants to design, mutate, and cloud-sync Webstudio projects offline with full MCP tool support and no API limits.

Provides component information, usage guidelines, and code generation for AWS Cloudscape Design System in React, with search and pattern library capabilities.

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

Enables LLM-driven inspection, building, modification, and visual review of Adobe After Effects compositions through structured scene-level operations and a CEP-to-ExtendScript bridge.

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.

Transforms HTML into Figma designs using only the user’s design system, ensuring correct component usage or safe fallback to primitives, while continuously learning from each build to improve mapping accuracy and consistency.

MCP server that gives AI agents browser-based access to Mobbin for design research, screen discovery, and screenshot collection through automated browser control.

Injects the Code-Me brand identity, tone, and visual guidelines into LLMs with zero latency using built-in context files.

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.

Maps design components, tokens, and patterns to their code implementations, providing AI coding agents with exact-match resolution across any design tool and framework. Enables agents to reliably discover and reuse existing components across React, Vue, Flutter, SwiftUI, and more.

Provides 8 MCP tools for frontend design: load design system, generate components, scaffold pages, review consistency, extract tokens, check WCAG 2.2 AA, test responsiveness, and export to Figma.

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.

MCP server for ingesting UI screenshots, Figma MCP node JSON, or hybrid Figma-plus-screenshot sources into a cross-platform design-to-code artifact pipeline.

Generates editable Excalidraw diagram files from natural language descriptions of systems and architectures.

Transforms Figma design data into a compact, LLM-friendly format for code generation, reducing size by 99.5% while preserving UI-critical information.

Enables AI assistants to control Figma in real-time through Model Context Protocol, allowing design creation, editing, and reading operations directly from VS Code.

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 assistants to inspect, modify, export, and validate design documents with 47 tools covering design, code generation, branding, and print/mockup workflows.