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rUv edited this page Sep 10, 2025 · 5 revisions

🚀 Complete Integration Tutorial: Claude Flow + Flow Nexus + ruv-swarm

📋 Table of Contents

  1. Overview
  2. Prerequisites
  3. Quick Start
  4. Step-by-Step Setup
  5. Integration Patterns
  6. Practical Examples
  7. Performance Optimization
  8. Troubleshooting
  9. Advanced Use Cases

🎯 Overview

This tutorial demonstrates how to integrate three powerful AI orchestration systems:

  • Claude Flow: Local AI orchestration with 87 MCP tools and SPARC methodology
  • Flow Nexus: Cloud-native platform with E2B sandboxes and distributed computing
  • ruv-swarm: WebAssembly-accelerated multi-agent system with neural networks

Benefits of Integration

✅ 3-10x Performance: WASM acceleration for neural computations
✅ Unified Interface: 150+ MCP tools through single protocol
✅ Cost Efficiency: Local development + cloud scaling
✅ Cognitive Intelligence: 5 adaptive thinking patterns
✅ Seamless Deployment: Local → Cloud migration path

🔧 Prerequisites

Required Software

# Node.js 18+ and npm
node --version  # v18.0.0+
npm --version   # 9.0.0+

# Claude CLI (latest)
npm install -g @anthropic-ai/claude-cli@latest

# Git for version control
git --version

Account Requirements

  • Flow Nexus Account: Register at https://flow-nexus.ruv.io
  • GitHub Account: For repository access
  • Claude API Access: For Claude Code integration

⚡ Quick Start

1. Install Claude Flow

# Install latest alpha version
npm install -g claude-flow@alpha

# Verify installation
npx claude-flow@alpha --version

2. Configure MCP Servers

# Add all three MCP servers
claude mcp add claude-flow npx claude-flow@alpha mcp start
claude mcp add flow-nexus npx flow-nexus mcp start
claude mcp add ruv-swarm npx ruv-swarm mcp start

# Verify MCP setup
claude mcp list

3. Test Integration

# Quick integration test
npx claude-flow@alpha sparc run test "Integration verification"

🛠️ Step-by-Step Setup

Step 1: Flow Nexus Authentication

// Login to Flow Nexus cloud platform
mcp__flow-nexus__user_login({
  email: "your-email@domain.com",
  password: "your-password"
})

// Check your credit balance
mcp__flow-nexus__check_balance()

Step 2: Initialize Local ruv-swarm

// Start local WASM-accelerated swarm
mcp__ruv-swarm__swarm_init({
  topology: "mesh",
  maxAgents: 5,
  strategy: "adaptive"
})

// Spawn intelligent agents
mcp__ruv-swarm__agent_spawn({
  type: "researcher",
  capabilities: ["neural_analysis", "cognitive_patterns"]
})

Step 3: Deploy Cloud Infrastructure

// Initialize cloud swarm with E2B sandboxes
mcp__flow-nexus__swarm_init({
  topology: "mesh",
  maxAgents: 10,
  strategy: "balanced"
})

// Create development sandbox
mcp__flow-nexus__sandbox_create({
  template: "node",
  name: "dev-environment",
  env_vars: {
    "NODE_ENV": "development",
    "API_KEY": "your-api-key"
  }
})

Step 4: Orchestrate with Claude Flow

# Use SPARC methodology for systematic development
npx claude-flow@alpha sparc run dev "Full-stack application"

# Enable coordination hooks
npx claude-flow@alpha hooks session-start --integration-mode

🔗 Integration Patterns

Pattern 1: Local Development Workflow

# 1. Design with SPARC
npx claude-flow@alpha sparc run architecture "E-commerce API"

# 2. Prototype with ruv-swarm
mcp__ruv-swarm__task_orchestrate({
  task: "Create API endpoints",
  strategy: "parallel",
  priority: "high"
})

# 3. Test locally
npx claude-flow@alpha sparc run test "API validation"

Pattern 2: Neural Network Development

// Local experimentation
mcp__ruv-swarm__neural_train({
  pattern_type: "classification",
  training_data: "local_dataset.json",
  epochs: 50
})

// Cloud distributed training
mcp__flow-nexus__neural_cluster_init({
  name: "production-cluster",
  architecture: "transformer",
  nodes: 5
})

mcp__flow-nexus__neural_train_distributed({
  cluster_id: "production-cluster",
  dataset: "large_training_set",
  epochs: 100,
  federated: true
})

Pattern 3: Full-Stack Deployment

// 1. Local development
mcp__ruv-swarm__swarm_init({topology: "mesh"})

// 2. Cloud staging
mcp__flow-nexus__sandbox_create({
  template: "nextjs",
  name: "staging-app"
})

// 3. Production deployment
mcp__flow-nexus__workflow_create({
  name: "Production Deploy",
  steps: [
    {action: "test", agent_type: "tester"},
    {action: "build", agent_type: "builder"},
    {action: "deploy", agent_type: "deployer"}
  ],
  triggers: ["github_push"]
})

💡 Practical Examples

Example 1: AI-Powered Code Review

# Setup review swarm
npx claude-flow@alpha sparc batch "review,test,optimize" "Code quality check"

# Deploy review agents
mcp__ruv-swarm__agent_spawn({
  type: "reviewer",
  capabilities: ["code_analysis", "security_scan", "performance_check"]
})

# Cloud validation
mcp__flow-nexus__sandbox_create({
  template: "python",
  name: "code-review-env"
})

Example 2: Real-Time Analytics Dashboard

// Neural pattern recognition
mcp__ruv-swarm__neural_patterns({
  action: "analyze",
  operation: "user_behavior_analysis"
})

// Cloud data processing
mcp__flow-nexus__workflow_create({
  name: "Analytics Pipeline",
  steps: [
    {action: "collect", source: "user_events"},
    {action: "process", agent_type: "analyst"},
    {action: "visualize", agent_type: "dashboard"}
  ]
})

// Real-time updates
mcp__flow-nexus__realtime_subscribe({
  table: "analytics_data",
  event: "*"
})

Example 3: Automated Testing Suite

# Comprehensive testing with all systems
npx claude-flow@alpha sparc run test "Full application suite"

# Parallel test execution
mcp__ruv-swarm__task_orchestrate({
  task: "Run unit tests",
  strategy: "parallel",
  maxAgents: 3
})

# Cloud integration testing
mcp__flow-nexus__sandbox_execute({
  sandbox_id: "test-env",
  code: "npm run test:integration",
  timeout: 300
})

⚡ Performance Optimization

WASM Acceleration Tips

// Optimize ruv-swarm performance
mcp__ruv-swarm__features_detect({component: "neural"})

// Check SIMD support
mcp__ruv-swarm__benchmark_run({
  type: "neural",
  iterations: 10
})

// Memory optimization
mcp__ruv-swarm__memory_usage({
  action: "analyze",
  namespace: "performance"
})

Cloud Resource Optimization

// Monitor Flow Nexus usage
mcp__flow-nexus__check_balance()

// Optimize sandbox usage
mcp__flow-nexus__sandbox_list({status: "running"})

// Auto-scaling configuration
mcp__flow-nexus__swarm_scale({
  swarm_id: "production",
  target_agents: 8
})

Claude Flow Coordination

# Performance monitoring
npx claude-flow@alpha hooks post-task --analyze-performance true

# Memory management
npx claude-flow@alpha hooks session-restore --optimize-memory

# Batch operations for efficiency
npx claude-flow@alpha sparc batch "code,tdd,devops" "Optimized pipeline"

🔧 Troubleshooting

Common Issues

1. Authentication Errors

# Check MCP server status
claude mcp list

# Remove and re-add MCP servers
claude mcp remove claude-flow
claude mcp remove flow-nexus
claude mcp remove ruv-swarm

# Re-add MCP servers
claude mcp add claude-flow npx claude-flow@alpha mcp start
claude mcp add flow-nexus npx flow-nexus mcp start
claude mcp add ruv-swarm npx ruv-swarm mcp start

# Re-authenticate Flow Nexus
mcp__flow-nexus__auth_status()

2. WASM Module Loading Issues

// Check ruv-swarm features
mcp__ruv-swarm__features_detect()

// Verify WASM support
mcp__ruv-swarm__swarm_status({verbose: true})

// Reload modules if needed
mcp__ruv-swarm__memory_usage({action: "clear"})

3. Cloud Sandbox Problems

// Check sandbox status
mcp__flow-nexus__sandbox_status({sandbox_id: "your-sandbox"})

// View logs
mcp__flow-nexus__sandbox_logs({
  sandbox_id: "your-sandbox",
  lines: 50
})

// Restart if needed
mcp__flow-nexus__sandbox_stop({sandbox_id: "problematic-sandbox"})

Performance Issues

Slow Agent Spawning

# Analyze performance metrics
npx claude-flow@alpha hooks post-task --analyze-performance

# Optimize agent count
mcp__ruv-swarm__swarm_scale({target_agents: 3})

# Use batch operations
npx claude-flow@alpha sparc pipeline "Optimized workflow"

High Memory Usage

// Monitor memory
mcp__ruv-swarm__memory_usage({detail: "full"})

// Clear unused resources
mcp__flow-nexus__sandbox_delete({sandbox_id: "unused-sandbox"})

# Optimize WASM modules
mcp__ruv-swarm__benchmark_run({type: "memory"})

🎯 Advanced Use Cases

Enterprise-Scale Development

# Multi-team coordination
npx claude-flow@alpha sparc batch "architecture,backend,frontend,testing" "Enterprise app"

# Distributed neural training
mcp__flow-nexus__neural_cluster_init({
  name: "enterprise-ai",
  nodes: 20,
  architecture: "transformer"
})

# Production monitoring
mcp__flow-nexus__workflow_create({
  name: "Production Monitor",
  triggers: ["system_alert", "performance_threshold"]
})

Research and Development

// Experimental neural patterns
mcp__ruv-swarm__neural_patterns({
  action: "experiment",
  patterns: ["lateral", "divergent", "systems"]
})

// Cloud experimentation environment
mcp__flow-nexus__sandbox_create({
  template: "research",
  install_packages: ["tensorflow", "pytorch", "numpy"]
})

// Collaborative research
npx claude-flow@alpha hooks team-coordination --research-mode

DevOps Automation

# Complete CI/CD pipeline
npx claude-flow@alpha sparc pipeline "Automated deployment"

# Infrastructure as Code
mcp__flow-nexus__workflow_create({
  name: "Infrastructure Deploy",
  steps: [
    {action: "validate", agent_type: "validator"},
    {action: "provision", agent_type: "provisioner"},
    {action: "configure", agent_type: "configurator"},
    {action: "monitor", agent_type: "monitor"}
  ]
})

# Monitoring and alerting
mcp__flow-nexus__realtime_subscribe({
  table: "system_metrics",
  filter: "severity >= 'warning'"
})

📊 Success Metrics

Track your integration success with these KPIs:

Development Velocity

  • Setup Time: < 10 minutes for full integration
  • Agent Spawn Time: < 0.01ms (ruv-swarm benchmark)
  • Cloud Deployment: < 2 minutes for E2B sandbox

Performance Metrics

  • Neural Training: 3-10x speedup with WASM
  • Memory Usage: < 50MB for full stack
  • Cost Efficiency: 60% reduction through smart scaling

Quality Indicators

  • Test Coverage: Automated across all three systems
  • Error Rate: < 1% with proper error handling
  • Uptime: 99.9% with cloud redundancy

🎓 Next Steps

  1. Explore Advanced Features: Dive deeper into cognitive patterns and neural networks
  2. Scale Your Applications: Use Flow Nexus for production deployments
  3. Contribute: Add new integration patterns to the community
  4. Monitor Performance: Set up comprehensive monitoring and alerting

📚 Additional Resources

Tutorial Version: 1.0
Last Updated: September 10, 2025
Compatibility: Claude Flow v2.0.0-alpha.107+

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