ruvnet/claude-flow
🌊 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 support via MCP protocol. Ranked #1 in agent-based frameworks.
npx skills add ruvnet/claude-flowREADME
🌊 Claude-Flow v3: Enterprise AI Orchestration Platform
Production-ready multi-agent AI orchestration for Claude Code
Deploy 60+ specialized agents in coordinated swarms with self-learning capabilities, fault-tolerant consensus, and enterprise-grade security.
Getting into the Flow
Claude-Flow is a comprehensive AI agent orchestration framework that transforms Claude Code into a powerful multi-agent development platform. It enables teams to deploy, coordinate, and optimize specialized AI agents working together on complex software engineering tasks.
Self-Learning/Self-Optimizing Agent Architecture
User → Claude-Flow (CLI/MCP) → Router → Swarm → Agents → Memory → LLM Providers
↑ ↓
└──── Learning Loop ←──────┘
📐 Expanded Architecture — Full system diagram with RuVector intelligence
flowchart TB
subgraph USER["👤 User Layer"]
U[User]
end
subgraph ENTRY["🚪 Entry Layer"]
CLI[CLI / MCP Server]
AID[AIDefence Security]
end
subgraph ROUTING["🧭 Routing Layer"]
QL[Q-Learning Router]
MOE[MoE - 8 Experts]
SK[Skills - 42+]
HK[Hooks - 17]
end
subgraph SWARM["🐝 Swarm Coordination"]
TOPO[Topologies<br/>mesh/hier/ring/star]
CONS[Consensus<br/>Raft/BFT/Gossip/CRDT]
CLM[Claims<br/>Human-Agent Coord]
end
subgraph AGENTS["🤖 60+ Agents"]
AG1[coder]
AG2[tester]
AG3[reviewer]
AG4[architect]
AG5[security]
AG6[...]
end
subgraph RESOURCES["📦 Resources"]
MEM[(Memory<br/>AgentDB)]
PROV[Providers<br/>Claude/GPT/Gemini/Ollama]
WORK[Workers - 12<br/>ultralearn/audit/optimize]
end
subgraph RUVECTOR["🧠 RuVector Intelligence Layer"]
direction TB
subgraph ROW1[" "]
SONA[SONA<br/>Self-Optimize<br/><0.05ms]
EWC[EWC++<br/>No Forgetting]
FLASH[Flash Attention<br/>2.49-7.47x]
end
subgraph ROW2[" "]
HNSW[HNSW<br/>150x-12,500x faster]
RB[ReasoningBank<br/>Pattern Store]
HYP[Hyperbolic<br/>Poincaré]
end
subgraph ROW3[" "]
LORA[LoRA/Micro<br/>128x compress]
QUANT[Int8 Quant<br/>3.92x memory]
RL[9 RL Algos<br/>Q/SARSA/PPO/DQN]
end
end
subgraph LEARNING["🔄 Learning Loop"]
L1[RETRIEVE] --> L2[JUDGE] --> L3[DISTILL] --> L4[CONSOLIDATE] --> L5[ROUTE]
end
U --> CLI
CLI --> AID
AID --> QL & MOE & SK & HK
QL & MOE & SK & HK --> TOPO & CONS & CLM
TOPO & CONS & CLM --> AG1 & AG2 & AG3 & AG4 & AG5 & AG6
AG1 & AG2 & AG3 & AG4 & AG5 & AG6 --> MEM & PROV & WORK
MEM --> SONA & EWC & FLASH
SONA & EWC & FLASH --> HNSW & RB & HYP
HNSW & RB & HYP --> LORA & QUANT & RL
LORA & QUANT & RL --> L1
L5 -.->|loops back| QL
style RUVECTOR
...
