openmas 0.1.5

OpenMAS: Easily Build Smart Multi-Agent Systems

OpenMAS

Easily Build Smart Multi-Agent Systems

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.

Full Documentation: https://docs.openmas.ai

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.

Model Context Protocol (MCP) Support

OpenMAS now supports MCP 1.7.1, providing a more stable and resilient integration with Anthropic's Model Context Protocol. The MCP integration allows agents to:

• Call tools provided by other agents
• Register tools for other agents to call
• Handle errors gracefully
• Communicate using either SSE (HTTP) or STDIO transports

See the MCP 1.7.1 Integration Guide for more details.

Installation

pip install openmas