"Testing Local AI Agents in LMStudio for Computer Use and Code Execution Tasks" matching MCP servers:

Enables MCP clients to administer a local LM Studio instance: loading, estimating, downloading, configuring and unloading models, running chat and embedding inference, diagnosing the server, engines and hardware, and managing MCP connectors with conflict-safe configuration. It also builds a local document index supporting citation-checked search and answers grounded in TXT, Markdown, PDF and DOCX files.

Computer Use

Exposes Anthropic's computer-use action surface (screenshot, click, move, keyboard, clipboard, batch) against a persistent desktop display via MCP stdio protocol. Enables AI agents to control a virtual desktop environment through natural language instructions.

An MCP server that enables AI agents to execute terminal commands and Python code on the host system, leveraging Agent Zero's battle-tested implementation with session management and smart output handling.

Safety middleware for AI computer use agents that monitors, enforces policies, and provides guardrails to enable safe desktop interaction.

Enables Windows desktop automation via MCP, allowing AI agents to control mouse, keyboard, and screen capture with the same interface as Anthropic's computer-use tool.

Enables an agent to see and operate a GNOME Wayland desktop like a human, including screenshots, mouse/keyboard control, accessibility tree access, OCR, clipboard, and audio listening.

Enables a constrained subagent to perform foreground GUI actions on Hyprland—observing, focusing windows, clicking, typing, scrolling, dragging, and managing the clipboard—under per-action approval with lease, audit log, and kill-switch gating.

Enables LLMs to control Windows desktops via local OCR, optional YOLO icon detection, and mouse/keyboard actions.

MCP server that gives any LLM a managed Docker workspace with live browser, terminal, code execution, document skills, and autonomous sub-agents.

A Windows computer-control MCP server for the DeepSeek Harness plugin that lets an agent take screenshots, magnify the view for low-vision assistance, move and click the mouse, type and press keys, enumerate and focus windows, and switch input methods. It also bridges to Krita to drive drawing, pressure-curve, liquify, smudge, and brush operations.

Enables efficient AI agent operations through sandboxed Python code execution with progressive tool discovery, PII tokenization, and skills persistence, achieving up to 98.7% token reduction by processing data in a sandbox rather than in context.

Enables MCP-speaking clients to control a real desktop via the computer_use tool, including clicking, typing, scrolling, dragging, key combos, app focus, and screen/accessibility capture. It also provides a verdict system that verifies whether input actions had their intended effect, with configurable approval modes.

Enables AI agents to drive a Linux/X11 desktop via AT-SPI accessibility-tree perception and element-level actions, avoiding screenshots and coordinate clicking.

Enables low-cost agent models to control Windows applications through a compact, state-safe proxy over Open Computer Use, reducing model-visible context by up to 99.8% with support for record/replay and reusable UI component memory.

Enables users to drive a selected Windows application toward a natural-language goal by reading the UI with local OCR/UIA and deciding next actions.

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.

Pixel-level browser automation MCP server that drives a real Chrome browser using screenshots as vision input and OS-level mouse/keyboard as output, evading anti-bot detection.

A multi-language testing automation server that enables AI assistants to discover, plan, and execute tests across six major programming languages. It provides comprehensive tools for repository scanning, automated test execution, and detailed coverage reporting.

Enables coding agents to drive any Windows desktop app through window-relative, token-efficient tools, with optional DeepSeek-powered vision.