OWL is a framework for multi-agent collaboration designed for real-world task automation, targeting developers and researchers interested in advanced AI agent systems. It aims to revolutionize AI agent collaboration by enabling dynamic interactions for more natural, efficient, and robust task automation.

How It Works

OWL leverages the CAMEL-AI Framework, employing a modular design with a comprehensive suite of toolkits that agents can utilize. It supports dynamic agent interactions and a Model Context Protocol (MCP) for standardized interaction with tools and data sources. This approach allows agents to perform tasks like web browsing, document parsing, code execution, and multimodal processing, enhancing their ability to automate complex real-world tasks.

Quick Start & Requirements

• Installation: Recommended via pip install -e . after cloning the repository and setting up a Python 3.10-3.12 virtual environment (using uv or venv). Docker installation is also supported.
• Prerequisites: Python 3.10-3.12, Node.js (for MCP), API keys for LLM providers (e.g., OpenAI, Gemini), and potentially Playwright dependencies.
• Setup: Requires setting environment variables for API keys. Estimated setup time is minimal if dependencies are met.
• Links: Documentation, Demo Video, Paper.

Highlighted Details

• Achieved #1 rank among open-source frameworks on the GAIA benchmark with a 69.09% score.
• Supports a wide array of toolkits, including browser automation, multimodal processing (image, video, audio), document parsing (PDF, DOCX), and code execution.
• Features a web-based UI built with Gradio for easier interaction and configuration.
• Integrates the Model Context Protocol (MCP) for standardized AI model-tool interactions.

Maintenance & Community

• Actively updated with recent additions including SearxNG, enhanced browser support, Gemini 2.5 Pro, OpenRouter, and MCP/File/Terminal toolkits.
• Community channels available via Discord and WeChat.

Licensing & Compatibility

• Licensed under Apache 2.0.
• Compatible with commercial use and closed-source linking.

Limitations & Caveats

• Optimal performance is strongly recommended with OpenAI models (GPT-4+); other models may yield significantly lower performance, especially on complex tasks.
• Browser interaction only occurs when OWL deems it necessary for task completion.