Can I use this skill with local models?

Yes, Browser Use supports local models via Ollama, allowing for completely free and unlimited browser automation without relying on external APIs.

Does it support structured data extraction?

Yes, it integrates with Pydantic to allow you to define extraction schemas, ensuring the agent returns structured, type-safe JSON data.

How does Browser Use compare to cloud-based automation tools?

Browser Use is open-source and self-hosted, which eliminates API rate limits and vendor lock-in while providing significantly faster execution for browser-specific tasks.

Is it possible to run this in a headless environment?

Absolutely. Browser Use includes configuration options for headless operation and provides ready-to-use Docker templates for server-side deployment.

Browser Use Integration

Name: Browser Use Integration
Author: adaptationio

byadaptationio

Browser Automation

Automates complex browser tasks and web scraping using the open-source Browser Use framework with any LLM.

About

This skill integrates the Browser Use framework into Claude Code, enabling powerful, self-hosted AI browser automation. It allows developers to build sophisticated web scraping agents, data extraction pipelines, and automated workflows that run on their own infrastructure. With support for major LLMs like Claude and GPT-4, as well as local models via Ollama, it provides a flexible, cost-effective alternative to cloud-dependent automation tools without the constraints of API rate limits or vendor lock-in.

Key Features

Structured data extraction using Pydantic schemas for type-safe results
Multi-LLM compatibility including Claude, GPT-4, and local Ollama models
0 GitHub stars
Self-hosted deployment with complete Docker and Docker Compose support
Advanced browser controls including headless mode, proxies, and session management
Robust error handling with built-in exponential backoff and timeout management

Use Cases

Complex web scraping and data extraction for market research and analysis
Automated end-to-end form filling and data entry across legacy web systems
Continuous price monitoring and competitor research across multiple e-commerce platforms

About

Key Features

Structured data extraction using Pydantic schemas for type-safe results
Multi-LLM compatibility including Claude, GPT-4, and local Ollama models
0 GitHub stars
Self-hosted deployment with complete Docker and Docker Compose support
Advanced browser controls including headless mode, proxies, and session management
Robust error handling with built-in exponential backoff and timeout management

Use Cases

Complex web scraping and data extraction for market research and analysis
Automated end-to-end form filling and data entry across legacy web systems
Continuous price monitoring and competitor research across multiple e-commerce platforms