Cooragent is an AI agent collaboration community designed for users to create and combine agents to complete complex tasks. It targets developers and researchers looking to build sophisticated AI workflows by enabling agent creation via natural language descriptions and facilitating collaboration between multiple agents.

How It Works

Cooragent operates in two modes: Agent Factory for creating agents from single-sentence descriptions, and Agent Workflow for orchestrating multiple agents to complete complex tasks. The Agent Factory uses a Planner to analyze requirements, select tools, and refine prompts for agent construction. Agent Workflow analyzes target tasks, selects suitable agents based on expertise, plans execution steps, and distributes tasks for collaborative completion. This approach aims to simplify agent development and enable emergent, complex behaviors through agent interaction.

Quick Start & Requirements

• Installation: Clone the repository and install via conda or uv with Python 3.12.
• Prerequisites: Python 3.12, playwright for browser tool usage. Requires API keys configured in a .env file.
• Setup: Basic setup involves cloning, environment creation, and dependency installation, estimated to be under 15 minutes.
• Documentation: FAQ

Highlighted Details

• Agent Factory: Creates agents from natural language descriptions, automating prompt engineering and tool selection.
• Agent Workflow: Orchestrates multi-agent collaboration for complex task execution.
• Langchain Compatibility: Deep integration allows leveraging existing Langchain components (Prompts, Chains, Memory, etc.).
• MCP Support: Adheres to the Model Context Protocol for standardized agent communication and context management.

Maintenance & Community

• Core Contributors: Zheng Wang, Jiachen Du, Shenzhi Wang, Yue Wu, Chi Zhang, Shiji Song, Gao Huang.
• Community: WeChat group for discussion.

Licensing & Compatibility

• License: Not explicitly stated in the README.
• Compatibility: Designed for integration with Langchain and supports the MCP protocol.

Limitations & Caveats

The README does not specify the project's license, which is crucial for commercial use or closed-source integration. The browser tool has a long wait time and is disabled by default. Windows platform support may require additional dependencies.