Clawd Cursor vs Screenbox

Clawd Cursor gives AI agents local control of desktop applications for GUI tasks where a native API or command-line interface is unavailable. It builds a screen map from accessibility data and OCR, assigning stable element IDs and confidence scores; screenshots are used only when needed. Agents can click and type, and actions can be checked against an expected outcome. The maker says every tool call goes through one safety layer and describes the software as local, localhost-only by default, and without telemetry. It supports Windows, macOS 12 or later, and Linux X11 or Wayland. Connections use stdio MCP or an HTTP MCP daemon at 127.0.0.1:3847/mcp. Listed hosts include Claude Code, Cursor, Windsurf, OpenClaw, and Zed. The tool offers seven recommended compound tools and 98 granular tools for compatibility and debugging; the maker says it works with any model. It is free and MIT licensed. Installation requires Node.js 20 or later. Desktop control needs one-time consent; macOS also requires Accessibility permission, while Screen Recording is optional for vision fallback.

Screenbox gives AI agents isolated virtual desktops with real browsers and desktop applications. Each desktop includes Chromium with DevTools and extensions, plus tools such as file managers, terminals, and office applications. Agents can use 21 MCP tools across more than 100 actions, including screenshots, OCR, clicks, typing, shell access, file operations, and clipboard control. It connects to MCP clients including Claude Desktop, Claude Code, and Cursor through stdio, streamable HTTP, or SSE. A web dashboard supports live viewing, agent management, snapshots, session logs, and a knowledge browser. Users can save and restore desktop states, including files and browser sessions, and clone desktops from templates. Activity can be viewed through RDP or noVNC, with mouse and keyboard control available. Desktops run in Docker containers with memory limits, network isolation, and no bind mounts; the maker cautions that they are not hardened sandboxes. The software is self-hosted and open source under AGPL-3.0. The maker says deployment data stays on the user's infrastructure and the software sends no telemetry to Screenbox or third parties. It requires about 2 GB of RAM per desktop and no GPU; idle desktops pause automatically.