Scrapybara

Scrapybara hosts remote desktop instances for AI agents, with a unified API for browser, filesystem and code sandbox workflows.

Разработка ИИ Агентов AI Инструменты Разработчика Агент программирования

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Overview

Scrapybara is a platform for hosting remote desktop instances for computer use agents. It is positioned for workflows that need a real desktop environment, browser access, filesystem access, and code execution rather than a purely text-based API.

The site describes a unified API that lets developers run agents with any model, connect low-level tools, and execute free-form computing tasks at scale. It also says the platform handles autoscaling, authentication, and system environments, which makes it aimed at production deployments and fleet-style automation.

Features

Remote desktop instances

Start remote desktop instances for computer use agents and use them as the execution environment for browser-driven or desktop-driven tasks.

Unified agent API

Use a single interface to run computer use workflows with structured outputs, multi-turn conversations, and custom tools.

Low-level tool access

Access browser, filesystem, and code sandbox controls from the same workflow so agents can interact with web pages, files, and code.

Python and TypeScript SDKs

Run workflows through Python or TypeScript with the shown `scrapybara` SDK installs and example code.

Autoscaling instance fleets

Start hundreds of instances in milliseconds and rely on the platform to handle orchestration and scaling.

Session and execution management

Save and load authenticated websites, pause and resume instances, and monitor execution with interactive streaming.

Use Cases

Computer-use automation
Run agents that need to click, type, browse, and interact with web apps inside a desktop environment.
Agentic development workflows
Execute code-backed workflows with browser, Bash, and edit tools inside remote Ubuntu instances.
Production agent operations
Set up production fleets of instances for repeatable automation jobs where autoscaling and authentication handling matter.
Long-running sessions
Work with authenticated sites, pause and resume sessions, and continue a workflow without rebuilding state from scratch.
Web research and scraping
Use the platform for structured scraping or research tasks where an agent needs browser access and tool use in one loop.

Pros and Cons

Pros

Supports remote desktop instances for computer use agents instead of only text-only workflows.
Offers one interface for structured outputs, multi-turn conversations, and custom tools.
Exposes browser, filesystem, and code sandbox controls for more granular agent actions.
Shows SDK examples in both Python and TypeScript.
Includes operational features such as autoscaling, authenticated access, and pause/resume.

Cons

The pricing page itself returns a 404, so plan details are taken from the homepage rather than a dedicated pricing page.
The source does not document security certifications, compliance standards, or deeper integration coverage beyond the homepage examples.

FAQ

What does Scrapybara do?

Scrapybara hosts remote desktop instances for computer use agents and exposes them through a unified API. The home page shows example workflows with Python and TypeScript SDKs, plus docs for getting started.

Which models or agent types does it support?

The source shows support for agents such as CUA and Claude Computer Use, and says developers can use any model through the unified API.

What environments and controls are available?

The homepage shows examples for Ubuntu instances and mentions a full Windows desktop as an instance type. It also lists browser, filesystem, and code sandbox access as low-level controls.

Is there a free tier or paid plans?

The pricing section on the homepage lists a free account tier, Basic, Pro, and Enterprise. It also says credit top-ups are available at $0.04 each or users can bring their own provider API key.

Is Scrapybara meant for production use?

The page states that Scrapybara handles autoscaling, authentication, and system environments so teams can deploy fleets of agents to production.