"A resource for skinning and rigging 3D models" matching MCP servers:

Provides agents with real Linux VMs to run commands, manage files, expose ports, and track costs, all through an ephemeral sandbox service.

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 agents to invoke a local Stata installation, including a Windows Stata build under Wine on Linux and macOS, for regression analysis, econometrics, paper replication, and empirical research with command guards, resource monitoring, and automatic log capture.

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

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.

A simple server that acts as a Master Control Program (MCP) for unified interaction with OpenAI and Anthropic (Claude) AI models through a single API endpoint.

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.

A server that integrates trained Random Forest models with Bee Framework, enabling ReAct interactivity for AI tools and agents.

A Python server implementing the Model Context Protocol to provide customizable prompt templates, resources, and tools that enhance LLM interactions in the continue.dev environment.

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.

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

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.

A Model Context Protocol server providing read-only access to MySQL databases, enabling LLMs to inspect database schemas and execute read-only queries.

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.

A Model Context Protocol server that provides read-only access to MySQL databases, enabling LLMs to inspect database schemas and execute read-only queries.

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.

A deployable Model Context Protocol server on Cloudflare Workers that runs without authentication requirements, allowing integration with AI models through the Cloudflare AI Playground or Claude Desktop.