💡 The paper introduces MetaChain, a fully automated framework that enables non technical users to create and deploy large language model agents using natural language alone. The current state of agent development frameworks such as LangChain and AutoGen requires extensive technical expertise, limiting their accessibility to only a small percentage of the global population. To address this challenge, MetaChain is designed as an autonomous agent operating system that comprises four key components: agentic system utilities, LLM powered actionable engine, self managing file system, and self play agent customization module. This system allows for efficient and dynamic creation and modification of tools, agents, and workflows without requiring coding skills or manual intervention. The framework is evaluated on the GAIA benchmark and demonstrates superior performance in generalist multi agent tasks, surpassing existing state of the art methods. Additionally, MetaChain shows consistently superior performance in retrieval augmented generation tasks compared to other large language model based solutions. The contributions of MetaChain are significant as it enables non technical users to build and deploy large language model agents, bridging the accessibility gap and opening up new possibilities for the widespread adoption of agent development frameworks.