"Computer Aided Design" matching MCP servers:

Provides a persistent Docker computer with terminal, file editing, and optional desktop GUI control through a Three.js interface.

A low-level computer-use MCP server that exposes raw desktop control (mouse, keyboard, shell, windows, processes, screenshots, etc.) to MCP clients like Claude Code and Codex.

Runs builds, tests, and benchmarks on a remote compute node via Tailscale and SSH, syncing projects with rsync.

Lets an agent load a design once into a long-lived OpenSTA session and then run static timing and power analysis through dedicated tools or arbitrary Tcl commands. Enables setup/hold slack, TNS/WNS, fmax, DRV, and power queries against the live session.

Enables Claude Code to interact with Linux X11 desktops by performing mouse actions, keyboard input, and capturing screenshots. It provides a suite of tools for automation tasks such as clicking, typing, and zooming on specific screen regions.

Enables AI agents to control virtual computers through Orgo, supporting computer management, screen actions, shell commands, file operations, streaming, and AI completions.

A local MCP server that lets users control their computer via voice commands, executing CLI tools, searching files, and receiving spoken feedback, with safety gating and confirmation.

Enables an assistant to control a Tandy Color Computer 3 emulated in MAME, allowing typing, disk operations, screen viewing, and state management.

Allows Claude desktop app to execute terminal commands and edit files on your computer through MCP, with features including command execution, process management, and diff-based file editing.

Enables MCP-capable AI clients to control a local computer over stdio with filesystem operations, ripgrep search, shell command execution, and persistent process sessions.

Enables full local computer control from MCP clients, including terminal commands, file system operations, application management, screen capture, and input device automation across Windows, macOS, and Linux.

Enables AI agents to search, update, manage files, and run terminal commands on a computer, with remote access via Streamable HTTP and OAuth 2.0 for integration with ChatGPT and web agents.

Enables AI agents running inside Terok containers to execute commands, drive persistent PTY sessions, and transfer files on pre-configured remote development containers over an authenticated host-side HTTP gateway. Agents reach these targets without ever holding host SSH credentials, and may only select targets permitted by their token's ACL.

Enables ChatGPT Desktop to read, search, edit and move files on your own computer, produce Word, Excel, PowerPoint, PDF and chart outputs, launch and manage terminal programs and processes, and run work on other machines you own by name over SSH. Everything runs locally under your own setup, with a Docker-isolated, offline document mode or a full-permission mode for file and code operations.

Enables voice assistants to start, monitor, message, and approve local Claude Code sessions on your computer, including sessions already open in a terminal. It exposes session management, recaps, approvals, and history search as MCP tools.

Enables Claude AI to securely access files, run shell commands, and search through a Windows computer with explicit user permission.

Enables MCP-capable AI assistants to control a Windows computer through GUI automation, file and process operations, PowerShell commands, durable background jobs, and binary file transfer with downloadable exports.

Enables local AI coding assistants to operate remote Linux EDA clusters over persistent SSH/SCP for digital IC design, simulation, formal property verification, UVM testbench generation, static linting, and Git-backed workspace synchronization.

Enables AI agents to design RF filters and SMPS-EMC from spec using three MCP servers that drive LTspice, Qucs-S, and scikit-rf, with closed-form synthesis, real-component optimization, and CISPR-aware compliance checking.

A lightweight server that enables AI agents to interact natively with the Windows operating system for tasks like UI automation and application control. It allows LLMs to perform file navigation, simulate user input, and manage windows without requiring specialized computer vision models.