Screenbox

Screenbox is self-hosted software that gives AI agents desktops with real browsers and applications. It suits developers and teams building computer-use workflows who need to supervise agents and preserve desktop state. Its breadth is useful, but Docker isolation should not be treated as a hardened security boundary.

Overview

Screenbox runs agent desktops in Docker and connects them to MCP clients including Claude Desktop, Claude Code, and Cursor. Support for stdio, streamable HTTP, and SSE gives teams several ways to integrate it, while the web dashboard brings desktop viewing, agent management, snapshots, session logs, and reusable knowledge into one place.

Human oversight is a meaningful part of the design: users can watch activity through RDP or noVNC and take mouse and keyboard control. Snapshots capture files and browser sessions, and desktops can be cloned from templates. These capabilities suit workflows where agents need intervention or a repeatable starting point, though operating the deployment and controlling access remain the user's responsibility.

Key features

• Broad desktop automation: 21 MCP tools span more than 100 actions, including screenshots, OCR, clicking, typing, shell, file I/O, and clipboard operations. That range is useful when an agent must work beyond a browser page, but it also makes careful API access configuration important.
• Real browser and applications: Each desktop includes Chromium with DevTools and extensions, plus applications such as file managers, terminals, and office tools. This supports workflows that depend on a full desktop environment rather than browser-only control.
• Reusable session knowledge: Screenbox can turn action logs into facts and inject them into future screenshot and look responses. This can help carry useful context across sessions, though it is specifically knowledge fed into those responses rather than a general promise of persistent agent memory.
• State and resource controls: Users can save and restore desktop state, clone from templates, and configure a time-to-live for acquired desktops. Idle desktops pause automatically, helping manage resource use without discarding the option to resume saved state.
• Isolation with limits: Containers have memory limits, network isolation, and no bind mounts. The maker warns they are not hardened sandboxes, so Screenbox is a poor fit for treating untrusted agent activity as securely contained. The maker also advises against public MCP API exposure and recommends localhost or VPN access; setup generates API tokens automatically.
• Self-hosted privacy: The maker says the software sends no telemetry or data to Screenbox or third parties and deployment data stays on the user's infrastructure. This is attractive for teams seeking local control, but also means they manage deployment and security configuration.

Pricing

Screenbox has one plan: Self-hosted at free. It is AGPL-3.0 open-source software running on your own infrastructure, with desktop app control, browser control, screen understanding, local deployment, and API access. There are no paid tiers described; the practical cost is running the infrastructure, and each desktop uses about 2 GB of RAM.

This plan fits users who can operate Docker-based services and want the full listed feature set without a subscription. It is less suitable for people seeking a managed deployment or a hardened sandbox, since the product is self-hosted and its container isolation has an explicit security caveat.

Platforms

Screenbox supports Linux, macOS, and Windows, as well as API, web, and self-hosted access. The maker's requirements are Linux with native Docker, macOS with Docker Desktop, and Windows with WSL2. Each desktop uses about 2 GB RAM and does not need a GPU, a practical consideration when sizing a host for multiple desktops.

Who it's for

Screenbox is best for developers and teams building or supervising AI computer-use agents who need real desktop applications, MCP integration, recoverable state, and local deployment. It is a stronger fit for controlled environments with careful API access than for public-facing deployments or workloads that require a hardened isolation boundary.

Pros and cons

• Pro: More than 100 actions across 21 MCP tools cover browser, desktop, shell, file, and clipboard work, making it suitable for varied computer-use workflows.
• Pro: Live viewing, human control, snapshots, and templates support oversight and repeatable sessions rather than leaving an agent's desktop opaque or disposable.
• Pro: Local self-hosting and the maker's no-telemetry claim appeal to users who want deployment data to remain on their own infrastructure.
• Con: Docker containers are not hardened sandboxes, which rules out treating them as a strong security boundary for untrusted activity.
• Con: Operators must manage deployment and API exposure themselves; public exposure is discouraged, and a desktop consumes about 2 GB RAM.

Alternatives

For a broader category comparison, browse AI Computer Use Agents.

• Claude Code is worth considering if you want its Free plan at no cost, but that plan does not include Claude Code.
• Computer Use OOTB may suit users looking for open-source software with API-based or locally running models on Windows and macOS.
• Gemini is an option for users who want a freemium app with image generation and editing, Deep Research, Gemini Live, Canvas, and Gems in its Free plan.
• QuickDesk may suit users who want an MIT-licensed open-source option with no feature restrictions or connection limits.
• agent-cu is an alternative for users seeking MIT-licensed software that runs locally with zero per-action cost.
• Clawd Cursor is another free, open-source option under the MIT license.
• Lapu AI may fit users who prefer a freemium agent with a Free plan and a paid Premium tier.
• open-computer-use is an alternative for users seeking MIT-licensed software that runs locally across macOS, Windows, and Linux.

Verdict

Choose Screenbox if you are building computer-use agents and want a free, self-hosted desktop environment with broad MCP control, live human oversight, and restorable sessions. Look elsewhere if you need a hardened sandbox or a managed service: Screenbox's maker explicitly limits its container security, and deployment remains your responsibility.