Multi-agent collaboration frameworks — CrewAI, AutoGen, MetaGPT, OpenAI Swarm and more. Explore how multiple AI agents divide tasks, coordinate roles, schedule work, and orchestrate conversations to solve complex jobs together.
Agency Agents is a curated collection of specialized AI agent personas with prompts, tools, and best practices for assembling multi-agent teams.
100+ AI Agent and RAG apps you can actually run — clone, customize, and ship. A great reference for quickly building LLM-powered applications.
Generate short videos with one click using AI LLM. Multi-step automation workflow from script generation to video composition.
TradingAgents is a multi-agent trading framework built with LangGraph that mirrors real-world trading firm dynamics with specialized LLM-powered agents for fundamental analysis, sentiment analysis, risk management, and more.
OpenHands is an open-source AI software engineering agent platform that can automatically execute development tasks, modify code, and support collaborative iteration.
Multi-agent swarm intelligence engine that extracts seed information from the real world, constructs a high-fidelity parallel digital world with thousands of agents, and predicts future trajectories through social evolution simulations.
The Multi-Agent Framework for building the first AI Software Company, enabling natural language programming with multi-role collaboration for automated requirement analysis, design, coding, and testing.
The leading agent orchestration platform for Claude. Deploy intelligent multi-agent swarms, coordinate autonomous workflows, and build conversational AI systems. Features enterprise-grade architecture, distributed swarm intelligence, RAG integration, and native Claude Code/Codex integration.
Microsoft AutoGen is a multi-agent conversation framework that lets you create multiple agents to collaborate through dialogue and solve complex tasks.
CrewAI is a multi-agent framework for orchestrating role-playing, autonomous AI agents that collaborate like a team to tackle complex tasks.
World's first open-source, agentic video production system with 12 pipelines, 52 tools, and 500+ agent skills. Turn your AI coding assistant into a full video production studio.
CowAgent (formerly chatgpt-on-wechat) is a powerful AI assistant framework built on LLMs with autonomous planning, tool use, long-term memory, multi-agent collaboration, and multi-channel integration for WeChat, Feishu, DingTalk, and more.
An accessible multi-agent sentiment analysis assistant that breaks filter bubbles, reveals true public opinion, and predicts trends — built from scratch without external frameworks.
Intelligent automation and multi-agent orchestration for Claude Code. Supports automated workflows, task coordination, and intelligent agent system building.
Teams-first multi-agent orchestration for Claude Code. Designed for team collaboration with support for multi-agent coordination, task distribution, and result integration to enhance team AI development efficiency.
A curated collection of 500 AI agent use cases across industries including healthcare, finance, education, and retail. Showcases practical applications with open-source project links.
DeepTutor: Agent-Native Personalized Learning Assistant.
ChatDev 2.0 enables full-lifecycle software development through LLM-powered multi-agent collaboration, simulating role-based teamwork in a virtual software company.
A multi-agent LLM-powered Chinese financial trading framework, enhanced Chinese version of TradingAgents with multi-source market data, real-time news, and LLM decision-making.
Vibe-Trading is an open-source personal trading agent stack that combines LLMs, MCP tooling, and multi-agent workflows for algorithmic trading and backtesting.
A curated list of AI autonomous agents. A comprehensive collection of open-source agent projects for discovering and understanding the agent ecosystem.
Open-source multi-agent framework from Alibaba, enabling the construction of observable and interpretable agents with rich distributed capabilities.
A2A (Agent-to-Agent) Protocol is an open protocol by Google enabling interoperability and collaborative communication between AI agents built across different frameworks and vendors.
GenAI Agents is a comprehensive collection of 50+ tutorials and implementations for Generative AI Agent techniques, from basic conversational bots to complex multi-agent systems.
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A systematic guide to seven tool-call fault tolerance patterns: timeout hierarchy, exponential backoff with jitter, circuit breakers, fallback provider chains, recoverable error classification, structured validation, and idempotency keys -- keeping agents stable in unstable real-world environments.
Most agent workflows fail at the orchestration layer, not the model. A practical comparison of DAG, state machine, and visual builder approaches with production-ready code for error handling, human approval gates, and conditional branching.
An in-depth comparison of mainstream AI agent frameworks including LangChain, LangGraph, CrewAI, and AutoGen to help you choose the best development stack.
A 2026 comparison of the most worthwhile AutoGPT alternatives — OpenHands, MetaGPT, Agency Swarm, CrewAI, AutoGen, BabyAGI — covering autonomy, controllability, production maturity, cost, and observability, and explaining why 'autonomous agents' are no longer mainstream in 2026, and how alternatives solve AutoGPT's core problems.
A step-by-step tutorial for installing and running AutoGPT locally, including environment setup, Docker deployment, and common troubleshooting.
A practical 2026 comparison of the top AI agent frameworks — LangGraph, CrewAI, AutoGen, OpenAI Agents SDK, Google ADK, Microsoft Agent Framework, Mastra, and Claude Agent SDK. Covers architecture philosophy, production maturity, multi-language support, observability, and team fit, with a selection decision tree.