The Revit MCP server is a TypeScript - based bridge service that enables real - time model data interaction between Claude AI and Autodesk Revit

Revit MCP integration is a bridge connecting Autodesk Revit and AI assistants, enabling model interaction through natural language.

An experimental Model Context Protocol server based on Node.js that provides access to the Autodesk Platform Services API and implements fine-grained access control through the Secure Service Accounts feature.

The Maya MCP Server project implements the Model Context Protocol (MCP), allowing AI assistants to control Autodesk Maya through natural language. This project features a lightweight design, does not require installing plugins in Maya, communicates via Maya's default MEL script port, and supports dynamically adding new tool functions.

This is an MCP server plugin developed for Autodesk Fusion 360, enabling AI assistants to directly interact with Fusion 360 through the MCP protocol, achieving functions such as design information acquisition, element modification, and CAD task prompting.

The Revit - MCP tool library provides comprehensive automated interaction functions for Autodesk Revit, enabling deep integration between AI assistants and Revit via the MCP protocol.

Implementation of the Maya MCP server, an AI assistant tool for controlling Autodesk Maya through natural language

This project implements an MCP server that interacts with Autodesk platform service documentation, focusing on the Model Derivative API and supporting the invocation of Autodesk APIs through tools such as Cursor or Claude.

The Fusion 360 MCP Server is a middleware that connects Cline and Autodesk Fusion 360. It exposes Fusion 360 toolbar commands as callable APIs and supports generating executable Python scripts through natural language parsing.

This project provides an MCP server based on FastMCP, enabling LLM agents to interact with Autodesk ShotGrid through the REST API, supporting querying and managing entities such as projects, assets, and tasks, and is suitable for LLM workflow integration.