Aworld
Search, understand, reproduce, and improve an idea with ease
What is Aworld?
Aworld is a Model Context Protocol (MCP) server that allows AI assistants like Claude, Cursor, and VS Code to search, understand, reproduce, and improve an idea with ease
Search, understand, reproduce, and improve an idea with ease
This server falls under the Coding Agents category on MCPgee, the world's largest MCP server directory with 33,000+ servers.
Features
- Search, understand, reproduce, and improve an idea with ease
Use Cases
Maintainer
Works with
Installation
Manual Installation
npx aworldConfiguration
Configuration Details
claude_desktop_config.json
Performance
Response Metrics
Resource Usage
How to Set Up and Use Aworld
AWorld is an open-source multi-agent framework and MCP server that provides an environment for AI agents to search, understand, reproduce, and iteratively improve ideas and software projects. It orchestrates specialized agents — including a Developer Agent for coding, an Evaluator Agent for quality assessment, and media generation agents for video, audio, and images — within an automated evolution loop that builds, evaluates, and refines outputs until quality targets are met. Researchers and developers working on automated software generation, RL-based agent training, and benchmark evaluation (GAIA, BrowseComp, xBench) use AWorld as their agent runtime.
Prerequisites
- Python 3.11+ installed (the framework requires 3.11 specifically)
- Conda package manager for environment isolation
- An MCP-compatible AI client such as Claude Desktop or Claude Code
- API keys for the LLM providers you want to use (configured via .env file)
- Git, to clone the AWorld repository
Clone the repository and create a conda environment
Clone AWorld from GitHub and create an isolated Python 3.11 conda environment. The framework requires Python 3.11 specifically.
git clone https://github.com/inclusionAI/AWorld && cd AWorld
conda create -n aworld_env python=3.11 -y
conda activate aworld_envInstall AWorld and the CLI
Install the main AWorld package and the aworld-cli tool in development mode so you have access to all commands.
pip install -e .
cd aworld-cli && pip install -e .Configure your LLM provider and API keys
Run the interactive CLI configuration to set up your model provider and API credentials. Alternatively, create a .env file in your working directory with the required environment variables.
aworld-cli --configStart the AWorld MCP server
Launch AWorld as an MCP server so your AI client can delegate tasks to the multi-agent system. The server exposes the framework's agent capabilities as MCP tools.
aworld-cli --mcpConfigure your AI client
Add the AWorld MCP server to your claude_desktop_config.json so Claude or another MCP client can invoke AWorld's multi-agent capabilities.
{
"mcpServers": {
"aworld": {
"command": "aworld-cli",
"args": ["--mcp"]
}
}
}Run an evolution loop task
Ask the AI assistant to use AWorld to build and iteratively improve a project. The evolution loop will automatically delegate to the Developer Agent, score the output with the Evaluator Agent, and refine until quality targets are met.
Aworld Examples
Client configuration
Claude Desktop configuration for the AWorld MCP server using the aworld-cli command.
{
"mcpServers": {
"aworld": {
"command": "aworld-cli",
"args": ["--mcp"],
"env": {
"OPENAI_API_KEY": "your-openai-api-key"
}
}
}
}Prompts to try
Use these prompts in your AI client once the AWorld MCP server is running and configured.
- "Use AWorld to create a Python web scraper that extracts product prices from an e-commerce site"
- "Start an evolution loop to build a data visualization dashboard with a UI quality score above 0.85"
- "Search for and reproduce the algorithm described in this research paper abstract"
- "Use the Developer Agent to refactor my codebase and then have the Evaluator Agent score the improvements"Troubleshooting Aworld
aworld-cli command not found after installation
Ensure you have activated the conda environment ('conda activate aworld_env') before running aworld-cli. The CLI is installed in the environment's bin directory and will not be available in other environments or system Python.
Evolution loop fails without completing the task
Check your .env file to ensure LLM API keys are set correctly and the configured model is accessible. The evolution loop requires multiple sequential LLM calls; if a call fails mid-loop, the loop will abort. Increase API rate limits or switch to a model with higher throughput.
Agent generates code but evaluation scores remain low
The Evaluator Agent compares output against the stated quality criteria. Be more specific in your prompt about what 'quality' means (e.g., 'the UI must load in under 2 seconds and pass WCAG AA accessibility checks'). More concrete criteria lead to more targeted improvement cycles.
Frequently Asked Questions about Aworld
What is Aworld?
Aworld is a Model Context Protocol (MCP) server that search, understand, reproduce, and improve an idea with ease It connects AI assistants to external tools and data sources through a standardized interface.
How do I install Aworld?
Follow the installation instructions on the Aworld GitHub repository. Clone the repo, install dependencies, and add the server config to your AI client.
Which AI clients work with Aworld?
Aworld works with all major MCP-compatible AI clients including Claude Desktop, Claude Code, Cursor, VS Code (GitHub Copilot), Windsurf, and Cline.
Is Aworld free to use?
Yes, Aworld is open source and available under the MIT license. You can use it freely in both personal and commercial projects.
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Set Up Aworld in Your Editor
Choose your AI client for step-by-step setup instructions.
Quick Config Preview
Add this to your claude_desktop_config.json or .cursor/mcp.json
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