"Methods for Context and Data Analysis" matching MCP servers:

Reverse-engineers design videos and images into structured frontend implementation specifications using vision LLMs and FFMPEG for frame-level analysis.

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

An MCP server that gives AI coding tools access to Figma design data for accurate one-shot implementation of designs.

A Model Context Protocol (MCP) server that enhances Figma design integration by adding element position information to API responses, enabling AI assistants to better understand spatial relationships and convert designs to code more accurately.

Converts Lanhu design URLs into AI-ready implementation context including HTML+CSS (Tailwind), image downloads, design tokens, and guidance.

Loads your project's Tailwind CSS config and exposes tools for AI agents to query actual design tokens and validate class names, preventing hallucination of non-existent utilities.

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

Converts Figma designs into structured code context with token-aware styling, enabling AI agents to generate production-level frontend code.

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

An MCP server that gives AI coding agents access to Figma design data, enabling pixel-perfect implementation of designs through structured data extraction, image downloads, and design token retrieval.

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.

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.

Exposes tools to ingest FigJam boards, retrieve context summaries, and answer free-form questions about the board content.

Converts Figma design data into structured semantic analysis JSON and screenshots for AI agents to use in design-to-code workflows.

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.

Node.js MCP server enabling AI assistants to interact with Autodesk Revit for model operations, data queries, and sketch-to-building generation via LLM.

Connects Claude Desktop to a running FreeCAD instance, enabling document management, part creation and editing, direct Python execution, parts library insertion, FEM analysis, and 3D view screenshots.

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.