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AWorld

Facilitates the building, evaluation, and running of general multi-agent assistance systems.

About

AWorld is a framework designed to bridge the gap between theoretical Multi-Agent System (MAS) capabilities and practical real-world applications. It allows users to quickly prototype real-world scenarios and task automation with AI-powered agents, extending them into generic agents or agent teams. With features like multi-tool environment support, standardized protocols, and a client-server architecture, AWorld enables efficient benchmarking, model training, and collaborative development for multi-agent systems.

Key Features

  • Implements a client-server protocol compatible with Model Contest Protocol (MCP).
  • 131 GitHub stars
  • Enables delegation between multiple AI-powered agents.
  • Provides a framework for standardized benchmarking and model training.
  • Supports multiple environments including browsers, Android device simulation, shell, and file systems.
  • Offers environment interfaces following gymnasium standards.

Use Cases

  • Creating agentic prototypes for real-world scenarios.
  • Building and evaluating multi-agent systems for task automation.
  • Benchmarking agent capabilities under a unified protocol.