Magic Loops is a development platform that lets users combine large language models with code to build, run, and share simple automated workflows.
Magic Loops is a developer-focused platform for building lightweight automations that combine large language models (LLMs) with traditional code. It provides a structured way to design, run, and share “loops” that orchestrate prompts, APIs, and custom logic into repeatable workflows. The primary purpose of Magic Loops is to make it easy to turn ad-hoc AI experiments into robust, reusable tools and backend processes without heavy infrastructure work.
The platform lets you define workflows as code, mixing LLM calls with standard programming constructs such as conditionals, loops, and function calls. You can chain multiple model interactions, parse and transform outputs, and integrate external services via HTTP requests or custom scripts. Magic Loops supports parameterized inputs, environment variables, and configuration management so the same loop can be reused across different environments or projects. Versioning and sharing capabilities make it straightforward to iterate on workflows and collaborate with teammates.
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