Welcome to OpenMAS

OpenMAS streamlines asynchronous Multi-Agent System (MAS) development in Python. By providing a lightweight framework, standardized structure, and helpful CLI tools, it handles the foundational setup, freeing you to concentrate on what matters most: designing and implementing sophisticated agent behaviors.

Inspired by modern development ecosystems and driven by real-world use cases like coding and gaming agents, OpenMAS aims to streamline the entire MAS lifecycle, with particular attention to integrating communication protocols like the Model Context Protocol (MCP) alongside standard web protocols.

Key Features

• Simplified Agent Development: Build agents inheriting from BaseAgent with a clear asynchronous lifecycle (setup, run, shutdown).
• Flexible Communication: Pluggable communicators for HTTP, Model Context Protocol (SSE & Stdio), gRPC, MQTT, with lazy loading to keep dependencies minimal. Easily extend with custom communicators. See Communication.
• Structured Projects: Standardized directory layout (agents/, shared/, extensions/, packages/) generated by openmas init promotes modularity and maintainability. See Project Structure.
• Layered Configuration: Robust system loading configuration from files (openmas_project.yml, config/*.yml), .env, and environment variables. See Configuration Guide.
• Agent Reasoning Agnosticism: While BaseAgent inherently supports heuristic-based logic, OpenMAS facilitates integrating diverse reasoning mechanisms. Follow guides for LLM Integration (using official LLM client libraries like OpenAI, Anthropic, Google Gemini) or explore built-in support for BDI Patterns (including BdiAgent and SPADE-BDI integration examples).
• Workflow Implementation: Implement various agent interaction patterns (see Building Effective Agents). While specific helpers exist for the Orchestrator-Worker pattern, the core framework enables building custom workflows like prompt chaining, routing, and parallel execution, with more helpers planned for future releases. See Agent Patterns.
• Developer Workflow Tools: Use the openmas CLI tool for initializing projects (openmas init), validating configuration (openmas validate), running agents locally (openmas run), managing dependencies (openmas deps), and generating deployment artifacts (openmas generate-dockerfile, openmas generate-compose). See CLI Docs.
• Extensibility: Design encourages local project extensions (extensions/) and shareable external packages (packages/).
• Testing Utilities: Includes MockCommunicator and AgentTestHarness to facilitate unit and integration testing. See Testing Your Agents.

Getting Started

Ready to build your first agent?

1. Installation: Get OpenMAS installed in your environment. Go to Installation Guide
2. Quick Start: Walk through a simple example to create and run a basic agent. Go to Getting Started Guide

Explore Further

Dive deeper into specific aspects of OpenMAS:

• Core Concepts: Understand the fundamental ideas.
  • Design Philosophy
  • Architecture Overview
  • Project Structure
  • Configuration System
  • Communication Layer
• Guides: Learn how to use specific features and patterns.
  • Integrating with LLMs
  • Using MCP Integration
  • Agent Patterns & Workflows
  • Reasoning Integration (BDI)
  • Testing Your Agents
  • Deploying OpenMAS Systems
  • Development Workflow (Contributing)
• Examples: See practical, runnable code examples.
  • Examples Overview
  • Use Case: Chesspal.ai Refactoring
• Command Line Interface: Detailed reference for the openmas CLI tool. Go to CLI Docs
• API Reference: Detailed documentation for all framework modules and classes. Go to API Reference

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We hope OpenMAS helps you build powerful and well-structured Multi-Agent Systems!