Meta Claw

MetaClaw is an open-source AI agent framework developed by AIMING Lab at the University of North Carolina at Chapel Hill. At its core, MetaClaw enables AI agents to achieve self-evolution and meta-learning by inserting a transparent proxy between users and large language models (LLMs). Every daily conversation becomes a learning signal, allowing agents to continuously improve during real-world deployment rather than relying solely on offline training. Traditional reinforcement learning approaches require massive annotated datasets and expensive GPU clusters. MetaClaw eliminates these barriers. Through its innovative architecture, agents accumulate experience from real-time user interactions, automatically extract and inject new skills, and achieve continuous capability improvement — all without pre-built datasets or dedicated GPU infrastructure. The MetaClaw framework combines online reinforcement learning, skill injection, and intelligent scheduling into a unified system, providing a fundamentally new paradigm for building adaptive, autonomous AI agents that grow smarter with every interaction.