Open Source Mac Multi-Agent Systems
Sort By:
Multi-Agent Systems for Mac
View 19 business solutionsBrowse free open source Multi-Agent Systems and projects for Mac below. Use the toggles on the left to filter open source Multi-Agent Systems by OS, license, language, programming language, and project status.
-
$300 in Free Credit Towards Top Cloud ServicesStart your project in minutes. After credits run out, 20+ products include free monthly usage. Only pay when you're ready to scale.
-
Our Free Plans just got better! | Auth0You asked, we delivered! Auth0 is excited to expand our Free and Paid plans to include more options so you can focus on building, deploying, and scaling applications without having to worry about your security. Auth0 now, thank yourself later.
-
1
uAgents
A fast and lightweight framework for creating decentralized agents
uAgents is a library developed by Fetch.ai that allows for creating autonomous AI agents in Python. With simple and expressive decorators, you can have an agent that performs various tasks on a schedule or takes action on various events. -
2
Agent Orchestrator
Agentic orchestrator for parallel coding agents
Agent Orchestrator from Composio is an open-source orchestration layer designed to manage fleets of parallel AI coding agents working on a shared codebase. It enables each agent to operate independently in isolated git worktrees, handling tasks like fixing CI failures, addressing code review comments, and creating pull requests. The platform automates the coordination of multiple agents, reducing the need for manual oversight in complex development workflows. It supports a wide range of agents, runtimes, and tools, making it flexible and framework-agnostic. Through a centralized dashboard, developers can monitor progress, review outputs, and intervene only when human judgment is required. Agent Orchestrator transforms AI-assisted development into a scalable, autonomous system for continuous code improvement. -
3
Open AEA Framework
A framework for open autonomous economic agent (AEA) development
open-aea is an open-source framework for building autonomous software agents that can operate and interact independently on decentralized networks. Developed by Valory, it facilitates creating agents capable of economic transactions, communication, and smart contract interactions in Web3 ecosystems. -
4
MetaGPT
The Multi-Agent Framework
The Multi-Agent Framework: Given one line Requirement, return PRD, Design, Tasks, Repo. Assign different roles to GPTs to form a collaborative software entity for complex tasks. MetaGPT takes a one-line requirement as input and outputs user stories / competitive analysis/requirements/data structures / APIs / documents, etc. Internally, MetaGPT includes product managers/architects/project managers/engineers. It provides the entire process of a software company along with carefully orchestrated SOPs. -
Gemini 3 and 200+ AI Models on One PlatformBuild, govern, and optimize agents and models with Gemini Enterprise Agent Platform.
-
5
CAMEL AI
Finding the Scaling Law of Agents. A multi-agent framework
The rapid advancement of conversational and chat-based language models has led to remarkable progress in complex task-solving. However, their success heavily relies on human input to guide the conversation, which can be challenging and time-consuming. This paper explores the potential of building scalable techniques to facilitate autonomous cooperation among communicative agents and provide insight into their "cognitive" processes. To address the challenges of achieving autonomous cooperation, we propose a novel communicative agent framework named role-playing. Our approach involves using inception prompting to guide chat agents toward task completion while maintaining consistency with human intentions. We showcase how role-playing can be used to generate conversational data for studying the behaviors and capabilities of chat agents, providing a valuable resource for investigating conversational language models. -
6
KaibanJS
JS-native framework for building and managing multi-agent systems
JavaScript-native framework for building multi-agent AI systems. Multi-agent AI systems promise to revolutionize how we build interactive and intelligent applications. However, most AI frameworks cater to Python, leaving JavaScript developers at a disadvantage. KaibanJS fills this void by providing a first-of-its-kind, JavaScript-native framework designed specifically for building and integrating AI Agents. Harness the power of specialization by configuring AI agents to excel in distinct, critical functions within your projects. This approach enhances the effectiveness and efficiency of each task, moving beyond the limitations of generic AI. Just as professionals use specific tools to excel in their tasks, enable your AI agents to utilize tools like search engines, calculators, and more to perform specialized tasks with greater precision and efficiency. -
7
Open Autonomy
A framework for the creation of autonomous agent services
Open Autonomy is a framework that enables the development of autonomous economic agents (AEAs) capable of operating independently in various economic contexts. -
8
PraisonAI
PraisonAI application combines AutoGen and CrewAI or similar framework
PraisonAI application combines AutoGen and CrewAI or similar frameworks into a low-code solution for building and managing multi-agent LLM systems, focusing on simplicity, customization, and efficient human-agent collaboration. Chat with your ENTIRE Codebase. Praison AI, leveraging both AutoGen and CrewAI or any other agent framework, represents a low-code, centralized framework designed to simplify the creation and orchestration of multi-agent systems for various LLM applications, emphasizing ease of use, customization, and human-agent interaction. -
9
Jason is a fully-fledged interpreter for an extended version of AgentSpeak, a BDI agent-oriented logic programming language, and is implemented in Java. Using JADE a multi-agent system can be distributed over a network effortlessly. This project was moved to https://jason-lang.github.io
-
Enterprise-grade ITSM, for every businessFreshservice is an intuitive, AI-powered platform that helps IT, operations, and business teams deliver exceptional service without the usual complexity. Automate repetitive tasks, resolve issues faster, and provide seamless support across the organization. From managing incidents and assets to driving smarter decisions, Freshservice makes it easy to stay efficient and scale with confidence.
-
10
masmt
A frame work for Multi agent system development
MaSMT is a java based multi-agent system development framework, especially designed for development of English to Sinhala machine translation system. MaSMT also capable to develop any multi-agent based system through its architecture. Reference: B. Hettige, A. S. Karunananda, G. Rzevski, Multi-agent solution for managing complexity in English to Sinhala Machine Translation, International Journal of Design & Nature and Ecodynamics, Volume 11, Issue 2, 2016, 88 – 96. B. Hettige, A. S. Karunananda, G. Rzevski, ” MaSMT: A Multi-agent System Development Framework for English-Sinhala Machine Translation”, International Journal of Computational Linguistics and Natural Language Processing (IJCLNLP), Volume 2 Issue 7 July 2013. -
11
AEA Framework
A framework for autonomous economic agent (AEA) development
agents-aea by Fetch.ai is a framework for building autonomous economic agents (AEAs) that can act independently, communicate, and transact on decentralized networks. It focuses on enabling AI-driven agents to participate in digital marketplaces and ecosystems. -
12
AgentForge
Extensible AGI Framework
AgentForge is a framework for creating and deploying AI agents that can perform autonomous decision-making and task execution. It enables developers to define agent behaviors, train models, and integrate AI-powered automation into various applications. -
13
AgentUniverse
agentUniverse is a LLM multi-agent framework
AgentUniverse is a multi-agent AI framework that enables coordination between multiple intelligent agents for complex task execution and automation. -
14
AgentVerse
Designed to facilitate the deployment of multiple LLM-based agents
AgentVerse is designed to facilitate the deployment of multiple LLM-based agents in various applications, which primarily provides two frameworks: task-solving and simulation. -
15
Blackboard implements a lightweight, portable tuple space suitable for multi-agent system and distributed component design. Supports implicit invocation via content-filtered asynchronous events, blocking call semantics, and shared memory messaging.
-
16
CRAB
CRAB: Cross-environment Agent Benchmark for Multimodal Language Model
CRAB (Composable and Reusable Autonomous Bots) is a framework for building modular, reusable AI agents that can perform complex tasks in various domains. It focuses on creating AI-driven workflows that can be composed of multiple autonomous agents working together. -
17
Crimes Model
Multiagent system for simulation of crime rates behavior.
Multi-agent system developed in Repast Symphony 2.0, for the simulation of property crime rates behavior. -
18
DevOpsGPT
Multi agent system for AI-driven software development
Welcome to the AI Driven Software Development Automation Solution, abbreviated as DevOpsGPT. We combine LLM (Large Language Model) with DevOps tools to convert natural language requirements into working software. This innovative feature greatly improves development efficiency, shortens development cycles, and reduces communication costs, resulting in higher-quality software delivery. The automated software development process significantly reduces delivery time, accelerating software deployment and iterations. By accurately understanding user requirements, DevOpsGPT minimizes the risk of communication errors and misunderstandings, enhancing collaboration efficiency between development and business teams. DevOpsGPT generates code and performs validation, ensuring the quality and reliability of the delivered software. -
19
Multi-agent system that helps to create fail-safe distributed storage in SOHO LAN. Source code has been published to GitHub: https://github.com/savermyas/JSaverStorage
-
20
Jason (AgentSpeak) implementation for Robocup Rescue, including launcher, TCP/UDP connection and agents for FireBrigade, FireStation, AmbulanceTeam, AmbulanceCenter, PoliceForce and PoliceStation.
-
21
LLMStack
No-code multi-agent framework to build LLM Agents, workflows
LLMStack is a no-code platform for building generative AI agents, workflows and chatbots, connecting them to your data and business processes. Build tailor-made generative AI agents, applications and chatbots that cater to your unique needs by chaining multiple LLMs. Seamlessly integrate your own data, internal tools and GPT-powered models without any coding experience using LLMStack's no-code builder. Trigger your AI chains from Slack or Discord. Deploy to the cloud or on-premise. -
22
Langroid
Harness LLMs with Multi-Agent Programming
Given the remarkable abilities of recent Large Language Models (LLMs), there is an unprecedented opportunity to build intelligent applications powered by this transformative technology. The top question for any enterprise is: how best to harness the power of LLMs for complex applications? For technical and practical reasons, building LLM-powered applications is not as simple as throwing a task at an LLM system and expecting it to do it. Effectively leveraging LLMs at scale requires a principled programming framework. In particular, there is often a need to maintain multiple LLM conversations, each instructed in different ways, and "responsible" for different aspects of a task. -
23
LiteMultiAgent
The Library for LLM-based multi-agent applications
LiteMultiAgent is a lightweight and extensible multi-agent reinforcement learning (MARL) platform designed for rapid experimentation. It allows researchers to design and test coordination, competition, and collaboration scenarios in simulated environments. -
24
MASLua
Multi-agent system modeling with Lua
A framework to simulate systems of agents in Lua on a 2D grid map, with modules for describing agent behavior and communication. A working example of a taxi fleet is given. The "basic" version uses conventional belief-desire-intention module (BDI.lua) for agent programming and a textual I/O. The "basic_EFSSM" version uses only state-oriented programming for agents. (Available soon.) --- Ribas-Xirgo, Ll.: Multi-agent system model of taxi fleets. In Advances in Physical Agents II, Springer International Publishing, 2021. Proceedings of the 21st International Workshop of Physical Agents (WAF 2020), November 19-20, 2020, Alcalá de Henares, Madrid, Spain. -
25
MASyV (Multi-Agent System Visualization) enables one to write agent-based models/cellular automata, eg. in C, visualize them in real time & capture to movie file with MASyVs GUI & message passing lib. Includes examples: Hello World, ants, viral infection
