swarms
The Enterprise-Grade Multi-Agent Orchestration Framework. Website: https://swarms.ai
danghuangshangは、wanikuaが公開しているオープンソースのAIエージェントプロジェクトです(GitHub: wanikua/danghuangshang)。GitHubスターは2,702、フォークは256で、MITライセンスの下で公開されています。GitHubでの最終更新は2026年5月22日です。
Multi-agent court inspired by ancient China: specialized agents debate and decide.
Set up Danghuangshang with OpenClaw.
Assign specialized personas to agents.
Let agents deliberate on your question.
Review the coordinated conclusion.
Agents deliberate like officials.
Each agent brings a perspective.
Built on the OpenClaw runtime.
A novel coordination pattern.
MIT licensed experiment.
Ancient governance meets AI.
Download the source and move into the project folder.
git clone https://github.com/wanikua/danghuangshang.git
cd danghuangshangEvery project documents its own setup; start with install requirements.
cat README.md | head -60Follow the project’s launch command — Docker, pip, npm, or a binary release.
# see README for the exact launch commandIt is an open-source project at wanikua/danghuangshang with 256 forks.
Yes. MIT licensed.
Both: a working system built around a cultural concept.
It is designed to coordinate agents through OpenClaw.
Check the repo; it has Chinese roots with broader support.
The Enterprise-Grade Multi-Agent Orchestration Framework. Website: https://swarms.ai
Flexible and powerful framework for managing multiple AI agents and handling complex conversations
🌟 The Multi-Agent Framework: First AI Software Company, Towards Natural Language Programming
JavaScript framework for multi-agent systems with a Kanban-inspired design.
Autonomous AI agents for penetration testing — self-hosted, multi-agent, with a full web UI
Swarm — OpenAI's experimental framework for lightweight multi-agent orchestration with agents and handoffs, MIT
LibreAIカタログに掲載されたAIエージェントプロジェクトの中で最もスターの多いもの — danghuangshangが合わなかった場合に検討したい、現実的な候補リストです。
A personal AI that really does things — on any OS, with your data staying yours.
An agentic skills framework & software development methodology that works.
Agent harness optimization system with skills, memory and security for Claude Code, Codex and more
The agent that grows with you — a Python framework for adaptive AI agents.
DeepSeek's plugin-based agent harness where everything is a plugin.
カタログの中でdanghuangshangとスター数が近いAIエージェントプロジェクト — 前後の棚もそのまま見て回れます。
Sync your AI coding setup: skills, agents, rules, MCP, hooks, everywhere.
MCP aggregator, orchestrator, middleware and gateway in one Docker — compose many servers into one endpoint
Persistent memory layer for AI agents, backed by Markdown and Milvus.
Official agent skills that teach AI coding tools to work with Supabase.
Chinese Java course: build AI agents with Spring AI, RAG, MCP, and tool calling.
YAO: rigorous engineering, evaluation, and governance for reusable agent skills.