"Resources and Assistance for Website Design, Frontend UX Flow, and Backend Design" matching MCP servers:

Enables AI assistants to perform high-performance 3D CAD design, ultra-fast multi-view rendering, immutable versioned project management, and geometry/mesh verification for 3D printing on Windows.

Enables AI agents to generate dimensionally accurate mechanical parts (gears, enclosures, brackets, assemblies) in headless Blender from plain-English specs or JSON parameters, then verify them against manifold, bounding-box and print-production gates and export glTF/STL assets. It also scaffolds interactive Three.js CAD viewer pages with orbit controls, wireframe toggles and exploded-view scrubbing.

An MCP server that provides tools for frontend development, including i18n issue detection, OpenAPI type generation, and project structure analysis.

Enables secure execution of Python code, SQL queries, and metric fetching through MCP with ephemeral Docker sandboxing.

A Model Context Protocol server that enables Claude to execute Python code using boto3 to query and manage AWS resources directly from conversations.

Provides tools for frontend testing including code analysis, test generation, test execution, and React component testing for Jest and Cypress frameworks.

Enables safe, remote execution and management of user JavaScript scripts through a Rust-based backend, with change preview and confirmation before applying updates.

MCP server that exposes Ansible modules to AI agents with a search-schema-check-execute workflow, enabling safe ad-hoc runs via check mode by default. It provides tools to search modules, fetch schemas, run modules, and list collections.

A comprehensive system for managing AI-assisted agile development workflows with a modern, resource-based API using FastMCP.

Enables AI assistants and MCP-compatible editors to scaffold, edit, validate, compile, run, debug, and diff durable TypeScript workflows directly through conversation.

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.

Provides a remote coding environment for AI to publish static websites as live URLs, with live code editing and sandbox execution.

Provides AI assistants with a complete FPGA toolchain for HDL linting, simulation, synthesis, and place-and-route across various hardware targets. It features a GitHub-backed IP core registry that enables users to search for and import MIT-licensed cores directly through their chat interface.

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 enables AI agents to execute sandboxed JavaScript code to control external web applications in real-time. It utilizes WebSockets to synchronize script execution with frontend animations, allowing complex UI interactions to be handled in a single agent turn.

Enables coding agents to compile supplied files, run optional focused tests, and get static findings across ten programming languages, providing a deterministic feedback loop on the code they are about to return.

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 AI-assisted development for Webasyst framework projects, including creating and managing apps, plugins, themes, and configurations through natural language commands.

A production-ready foundation template for building Model Context Protocol (MCP) servers with FastAPI, featuring modular tools, comprehensive testing, and OpenShift deployment configurations. Includes automated transformation scripts to create custom domain-specific MCP servers.

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.

Enables compatible MCP AI tools to read, write, design windows, and run programs in the E-Language IDE.

A secure MCP gateway for Termux that exposes filesystem, shell, and Termux:API tools over a local HTTP endpoint with admin controls, job management, and upstream support.

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 LLMs to drive Blender through socket-based two-way communication, letting them create and modify 3D objects, apply materials, run Blender Python, and fetch or generate assets while visually verifying results. Supports prompt-assisted 3D modeling, scene creation, and manipulation.

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.

Enables AI assistants to operate directly inside a running Unity Editor project, creating scenes, generating scripts, simulating input, capturing screenshots, inspecting performance, and automating editor tasks through its built-in tools and resources.

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.

Gitbub mcp

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