"SketchUp application for creating 3D models" matching MCP servers:

Connects a locally running MCP-compatible assistant to SketchUp desktop, letting it check connection status and describe the current document and selection. Optionally enables explicitly approved, unsandboxed native Ruby scripting for deeper model access.

Enables AI clients to drive SketchUp Pro 2026 on a Windows host, including from WSL, by executing arbitrary Ruby in the active model, reading scene and selection details, and capturing viewport screenshots. It talks to a loopback TCP bridge inside SketchUp using a connect-per-command protocol for reliable, desync-free control.

Enables MCP clients to inspect and modify SketchUp models through a local authenticated bridge, covering entity creation and editing, geometry, materials, tags, cameras, scenes, transactions, snapshots, and file or view export. It also offers an optional full SketchUp Ruby API execution channel and batch operations for furniture, architectural, and analysis tasks.

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

Integration that connects Sketchup to Claude AI through the Model Context Protocol, allowing Claude to directly interact with and control Sketchup for prompt-assisted 3D modeling, scene creation, and manipulation.

A development server that automatically discovers and exposes tools from the src/tools directory, allowing you to create and run Machine Comprehension Protocol (MCP) services with either HTTP or STDIO transport methods.

A server that leverages the XMCP framework to discover and execute tools from the src/tools directory, supporting both SSE and STDIO transport methods for interaction.

A Model Context Protocol (MCP) server template designed for building structured tools, prompts, and resources with built-in support for HTTP and STDIO transports. It provides a standardized framework for developers to create and deploy AI-driven services using TypeScript and Zod schema validation.

Enables AI assistants to write and execute C# code directly inside Autodesk Civil 3D, using read-only and write tools plus reusable skill templates for drawing and civil object tasks.

Enables AI assistants to write and execute C# code directly inside Autodesk Civil 3D, providing full API access through code generation and execution.

Enable Claude (or any other LLM) to interactively debug your code (set breakpoints and evaluate expressions in stack frame). It's language-agnostic, assuming debugger console support and valid launch.json for debugging in VSCode.

MCP server that gives AI agents isolated, named Linux computers with stable IDs and lifecycle control. Supports multiple backends like Docker, Fly Machines, Modal, and E2B, with a dashboard for managing sandboxes.

Enables Claude Desktop to control FreeCAD for 3D CAD modeling, including creating, editing, and deleting objects, executing Python code, and running FEM analyses.

Connects MCP-compatible assistants to Blender to read scene and selection context, and optionally execute user-requested Python through Blender's native API when explicitly enabled.

A FastMCP server implementation that provides a standardized interface for accessing AI models hosted on Replicate's API, currently supporting image generation with customizable parameters.

A starter template for creating MCP servers that work with Puch AI, featuring ready-to-use tools for job searching and image processing. Includes examples for Bearer token authentication, OAuth integration with Google and GitHub, and demonstrates user-scoped data management.

It connects MCP-compatible assistants to Rhino 8 for checking status and describing the current selection, with optional explicitly enabled native Python scripting access.

Enables AI assistants to operate directly inside a running Unity Editor project, using built-in tools for scene creation, script generation, play mode automation, input simulation, and performance analysis.

Connects an MCP-compatible assistant running locally to a native Revit session through a pyRevit bridge, exposing document and selection context, status checks, and optionally unsandboxed IronPython scripting that can modify models and files.

Enables AI clients to interact with and control the Unity Editor through a Python MCP server bridge, allowing natural language-based Unity project manipulation.