Veilus Integrations

Claude Code is a developer-focused AI tool built to actively assist with real-world coding tasks inside the tools engineers already use. Instead of only completing lines of code, it understands full features, repositories, and workflows. Developers can run Claude Code from their terminal, IDE, Slack, or browser to ask questions, make changes, or debug issues. It automatically explores codebases to provide context-aware explanations and recommendations. This makes onboarding to new projects significantly faster and less error-prone. Claude Code can refactor large sections of code, run tests, and help resolve issues without jumping between platforms. It supports integrations with GitHub, GitLab, and common CLI utilities for end-to-end development workflows. Teams can use it to turn issues into pull requests with minimal manual effort. Claude Code is included in Anthropic’s Pro and Max plans with varying usage limits. Overall, it helps developers focus more on decision-making and less on repetitive implementation work.

Cursor is an AI-powered coding agent platform designed to help developers and teams build software more efficiently. The platform allows users to assign coding tasks to AI agents that can explore codebases, make changes, run tests, create demos, and deliver work for human review. Cursor supports agentic development, cloud agents, automations, code review, CLI workflows, Slack collaboration, terminal usage, and GitHub PR review. Its agents can run autonomously and in parallel, making it possible to work on multiple features, fixes, and maintenance tasks at once. Developers can use Cursor for targeted edits, full autonomous builds, repetitive task automation, repository maintenance, debugging, deployment preparation, and CI investigation. Cursor supports leading models from OpenAI, Anthropic, Gemini, SpaceXAI, and Cursor so teams can choose the best model for each task. Enterprise features are designed for secure, large-scale software development, with SOC 2 certification and adoption across major organizations. The platform also includes cloud agents that can work for hours or days on ambitious tasks across multiple repositories. By combining AI coding agents, parallel execution, model choice, editor workflows, terminal access, Slack collaboration, GitHub review, and enterprise controls, Cursor helps teams develop software faster.

Browser Use provides hosted AI agents and remote browser infrastructure for automating work on websites. It helps developers connect software to tasks such as signing into portals, completing forms, collecting information, and downloading documents, especially where no usable API exists. Browser Use Agents accepts natural-language tasks and operates a managed browser to carry them out. Teams can delegate multi-step website work without building and maintaining their own agent loop. Use cases include cross-site research, authenticated document collection, data extraction, and repetitive portal workflows. Browser Infrastructure supplies remote Chromium sessions for teams running their own agents, Playwright scripts, or Puppeteer automation. It combines browser stealth, residential proxy options, and automatic handling of supported CAPTCHAs. Developers retain control of their automation logic while Browser Use manages the browsers. The MIT-licensed browser-use Python library supports running and customizing agents in your own environment with local or cloud browsers. Browser Harness, CLI tools, SDKs, and Model Context Protocol (MCP) interfaces provide additional ways to give existing applications and agents browser capabilities. Cloud services use pay-as-you-go pricing with no required subscription and no expiry on purchased credits. Browser runtime starts at $0.02/hour; network traffic is charged separately. Hosted agents add model costs and a 20% service fee. Eligible signups receive a one-time $15 cloud credit. The open-source library is free to use, with model and infrastructure costs depending on your setup.

The Model Context Protocol (MCP) is a flexible, open-source framework that streamlines the interaction between AI models and external data sources. It enables developers to create complex workflows by connecting LLMs with databases, files, and web services, offering a standardized approach for AI applications. MCP’s client-server architecture ensures seamless integration, while its growing list of integrations makes it easy to connect with different LLM providers. The protocol is ideal for those looking to build scalable AI agents with strong data security practices.

LangChain provides a comprehensive framework that empowers developers to build and scale intelligent applications using large language models (LLMs). By integrating data and APIs, LangChain enables context-aware applications that can perform reasoning tasks. The suite includes LangGraph, a tool for orchestrating complex workflows, and LangSmith, a platform for monitoring and optimizing LLM-driven agents. LangChain supports the full lifecycle of LLM applications, offering tools to handle everything from initial design and deployment to post-launch performance management. Its flexibility makes it an ideal solution for businesses looking to enhance their applications with AI-powered reasoning and automation.

You can perform almost any task that you would typically handle manually in a web browser using Puppeteer! The lightweight version, known as Puppeteer-core, is designed for those who want to launch an existing browser installation or connect to a remote browser. It's crucial to ensure that the version of puppeteer-core you choose aligns with the browser version you plan to use. For individuals already acquainted with other browser testing frameworks, Puppeteer will seem quite familiar. You start by creating a Browser instance, opening web pages, and then using Puppeteer's API to manipulate those pages. By default, Puppeteer downloads a specific Chromium version, ensuring that its API functions correctly right from the start. To utilize Puppeteer with an alternative version of Chrome or Chromium, you simply need to specify the path to the executable when you create a Browser instance. This flexibility allows for a tailored testing experience that can adapt to different project requirements.

Playwright is compatible with all contemporary rendering engines, such as Chromium, WebKit, and Firefox. It enables testing across various operating systems like Windows, Linux, and macOS, whether locally or in continuous integration environments, and can operate in both headless and headed modes. The framework ensures that actions are only performed once elements are ready for interaction, and it includes a comprehensive set of introspection events. This synergy effectively removes the reliance on artificial timeouts, which are a common source of unreliable tests. Additionally, Playwright's assertions are tailored for the dynamic nature of the web, automatically reattempting checks until the specified criteria are fulfilled. Users can customize their test retry strategies and capture execution traces, videos, and screenshots to further mitigate instability. In terms of architecture, browsers execute web content from different origins in separate processes, allowing Playwright to align with modern browser frameworks and conduct tests out-of-process. This design choice helps to avoid the usual constraints associated with in-process test runners, ultimately enhancing testing efficiency and reliability. As a result, Playwright emerges as a robust solution for developers seeking to streamline their testing processes.

Stagehand is an innovative web automation framework powered by AI that significantly enhances the functionality of Playwright, allowing developers to control web browsers using simple natural language commands. Developed by Browserbase, it features three user-friendly APIs—act, extract, and observe—that build on Playwright's foundational page class, making the process of web automation more accessible. Developers can, for example, easily navigate to specific websites, locate elements such as input fields, retrieve targeted information like product costs, and execute actions such as adding products to shopping carts, all through conversational directives. This method streamlines the development of robust, self-sustaining, and repeatable web automation processes, minimizing the challenges and vulnerabilities commonly found in conventional approaches. Furthermore, Stagehand seamlessly integrates with existing Playwright code, ensuring that it fits effortlessly into ongoing projects. By harnessing the power of AI, it not only simplifies but also enhances the efficiency of managing browser automation tasks, ultimately leading to improved productivity for developers. This combination of ease-of-use and effectiveness sets Stagehand apart as a valuable tool in the realm of web automation.