"Testing Kubernetes Network Policies" matching MCP servers:

Enables users to automate the creation, editing, animation, and export of pixel-art game assets through a multi-agent pipeline that derives style specs and blueprints, generates Lua build scripts, and drives the canvas editor to produce .aseprite files, spritesheets, atlases, GIFs, and previews.

A Houdini MCP server fork for CsrLib-Houdini workflow, providing enhanced tools for scene management, node discovery, graph editing, and safe code execution with tiered security policies.

Exports Figma designs as ready-to-use HTML/CSS and validates pixel-perfect accuracy with image comparison and visual regression testing.

Connects LLM assistants to Autodesk Revit BIM models, enabling reading metadata, listing elements, creating geometry, batch parameter updates, and exporting schedules. Supports fake mode for testing without Revit and pyRevit mode for live integration.

An MCP server that lets AI assistants control Adobe Illustrator locally—running ExtendScript, capturing canvas screenshots, exporting artwork, and optionally remembering techniques—all without network activity.

Enables AI agents to control the DX12 Engine editor for game development, including scene editing, entity manipulation, and playback testing via natural language commands.

Provides deterministic, read-only design knowledge for AI coding agents to help them choose visual directions, plan UI states, and compose design tokens, all without network access.

Enables AI agents to spin up a fake After Effects bridge server, script its responses, and inspect incoming client requests for testing bridge client code without a real After Effects installation.

A local MCP server that renders nyyon's editorial diagrams and featured covers from a spec, without network requests.

Enables offline reading and rendering of Figma .fig files, allowing AI agents to extract design specs, export assets, and generate code without needing the Figma API or network access.

tdmcp is an open-source (MIT) Model Context Protocol server for TouchDesigner. You describe a visual in plain language and your AI assistant builds the real node network inside TouchDesigner, checks it for errors, and shows a preview — it ships an embedded operator knowledge base so the model uses real operators instead of guessing. TypeScript codebase, runs locally.

Enables AI models to create and manage various types of diagrams (flowcharts, UML, network diagrams, etc.) via the Model Context Protocol.

A local MCP bridge that lets AI agents build and edit real TouchDesigner networks by creating and wiring operators, setting parameters and expressions, validating the network, and viewing rendered image previews to iterate on results.

Enables users to capture TouchDesigner node network screenshots and ask Claude for context-aware analysis, diagnosis, and suggestions via MCP tools.