AI cloud station provides a one-click deployment solution for cloud-based IDE environments. It integrates top AI coding tools like Claude Code, Gemini CLI, and OpenAI Codex with modern development environments. Teams can collaborate securely and efficiently from anywhere.
git clone https://github.com/shareAI-lab/ai-cloud-station.gitThe ai-cloud-station skill is designed to streamline the setup of cloud-based integrated development environments (IDEs) for small to medium-sized startup teams. This skill integrates online VSCode, Claude Code, and Gemini, providing a comprehensive environment that allows developers to focus on coding without the hassle of manual configuration. By automating the setup process, teams can quickly get to work on their projects, enhancing productivity and collaboration. One of the key benefits of using ai-cloud-station is the significant reduction in time spent on environment configuration. Although the exact time savings are not quantified, the skill is designed to be implemented in just 30 minutes, allowing teams to allocate their resources more effectively. This is particularly advantageous for startups that often operate under tight deadlines and limited resources, as it enables them to launch and iterate on their products faster. This skill is ideal for developers, product managers, and AI practitioners who are looking to optimize their workflow automation. By simplifying the development environment setup, it allows teams to focus on building features and improving their applications rather than getting bogged down in technical setup tasks. Additionally, it can be particularly beneficial for teams that are adopting an AI-first approach, as it integrates seamlessly with AI tools and services, fostering a more efficient development process. Implementing ai-cloud-station requires intermediate technical skills, but once set up, it provides a robust platform for development. Practical use cases include rapid prototyping of applications, collaborative coding sessions, and integrating AI functionalities into projects. By leveraging this skill, teams can enhance their workflow automation and ensure that they are well-equipped to meet the demands of today’s fast-paced development landscape.
No install command available. Check the GitHub repository for manual installation instructions.
git clone https://github.com/shareAI-lab/ai-cloud-stationCopy the install command above and run it in your terminal.
Launch Claude Code, Cursor, or your preferred AI coding agent.
Use the prompt template or examples below to test the skill.
Adapt the skill to your specific use case and workflow.
Set up an AI cloud station for our team of [NUMBER] developers. We need integration with [TOOLS] and access to [REPOSITORIES]. Ensure the environment supports [PROGRAMMING_LANGUAGES] and includes [ADDITIONAL_REQUIREMENTS].
Your AI cloud station has been successfully deployed. Here are the details: Environment URL: https://cloudstation.ai/team/devops-2024 Access: Granted to all team members with @company.com email addresses Integrated Tools: Claude Code, Gemini CLI, OpenAI Codex Connected Repositories: GitHub (devops-2024 org), Bitbucket (marketing-team) Supported Languages: Python, JavaScript, Go, Rust Additional Features: Pre-configured CI/CD pipelines, Docker support, and real-time collaboration Your environment is ready for immediate use. All team members can access it through their browsers with their company credentials.
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