I built CloudHike: a backend your AI coding agent can set up over MCP

Описание и применение

Разработчики могут быстро развернуть полноценный бекенд, используя CloudHike и MCP, избавившись от ручной настройки баз данных, хранилищ и аутентификации.

Задача

AI coding agents can write full-stack code but struggle with backend provisioning—creating databases, storage, auth, email, and managing secrets—leading to lost momentum and multiple dashboards.

Результат

Developers can now set up complete backends in a single prompt, reducing manual configuration to a few clicks and keeping secrets out of source control.

Рабочий процесс

• Configure MCP server URL and API key in the editor
• Agent analyzes app code to determine required services
• Agent calls list_projects or create_project to obtain a project
• Agent calls deploy_services for needed services and waits until ready
• Agent calls get_environment to retrieve .env variables and writes them to .env.local
• Agent calls get_docs to fetch relevant documentation and generates connection code

Доказательства

My AI agent can write a whole Next.js app in an afternoon. Then it stops and hands the hard part back to me: make a Postgres database, set up a storage bucket, find a Redis instance, add auth, pick an email provider, and copy a dozen connection strings into .env.local without committing any of them.

Источник

CloudHike is a backend-as-a-service built for people who code with AI agents. Each project can have: Postgres, S3-compatible storage, Redis, Auth, Transactional email, Background jobs.

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The part I care about most is the remote MCP server. Once you add it to your editor, your agent can do the backend setup itself.

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With the server connected, open your app's folder and paste this prompt (it's from the docs): Use the cloudhike MCP tools to set up CloudHike.dev as the backend for this app.

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