flow-nexus-swarm

mcp__flow-nexus__agent_spawn({
  type: "researcher", // Options: researcher, coder, analyst, optimizer, coordinator
  name: "Lead Researcher",
  capabilities: ["web_search", "analysis", "summarization"]
})

mcp__flow-nexus__task_orchestrate({
  task: "Build a REST API with authentication and database integration",
  strategy: "parallel", // Options: parallel, sequential, adaptive
  maxAgents: 5,
  priority: "high" // Options: low, medium, high, critical
})

// Get detailed swarm status
mcp__flow-nexus__swarm_status({
  swarm_id: "optional-id" // Uses active swarm if not provided
})
 
// List all active swarms
mcp__flow-nexus__swarm_list({
  status: "active" // Options: active, destroyed, all
})
 
// Scale swarm up or down
mcp__flow-nexus__swarm_scale({
  target_agents: 10,
  swarm_id: "optional-id"
})
 
// Gracefully destroy swarm
mcp__flow-nexus__swarm_destroy({
  swarm_id: "optional-id"
})

mcp__flow-nexus__workflow_create({
  name: "CI/CD Pipeline",
  description: "Automated testing, building, and deployment",
  steps: [
    {
      id: "test",
      action: "run_tests",
      agent: "tester",
      parallel: true
    },
    {
      id: "build",
      action: "build_app",
      agent: "builder",
      depends_on: ["test"]
    },
    {
      id: "deploy",
      action: "deploy_prod",
      agent: "deployer",
      depends_on: ["build"]
    }
  ],
  triggers: ["push_to_main", "manual_trigger"],
  metadata: {
    priority: 10,
    retry_policy: "exponential_backoff"
  }
})

mcp__flow-nexus__workflow_execute({
  workflow_id: "workflow_id",
  input_data: {
    branch: "main",
    commit: "abc123",
    environment: "production"
  },
  async: true // Queue-based execution for long-running workflows
})

// Get workflow status and metrics
mcp__flow-nexus__workflow_status({
  workflow_id: "id",
  execution_id: "specific-run-id", // Optional
  include_metrics: true
})
 
// List workflows with filters
mcp__flow-nexus__workflow_list({
  status: "running", // Options: running, completed, failed, pending
  limit: 10,
  offset: 0
})
 
// Get complete audit trail
mcp__flow-nexus__workflow_audit_trail({
  workflow_id: "id",
  limit: 50,
  start_time: "2025-01-01T00:00:00Z"
})

mcp__flow-nexus__workflow_agent_assign({
  task_id: "task_id",
  agent_type: "coder", // Preferred agent type
  use_vector_similarity: true // AI-powered capability matching
})

mcp__flow-nexus__workflow_queue_status({
  queue_name: "optional-specific-queue",
  include_messages: true // Show pending messages
})

// 1. Initialize swarm with hierarchical topology
mcp__flow-nexus__swarm_init({
  topology: "hierarchical",
  maxAgents: 8,
  strategy: "specialized"
})
 
// 2. Spawn specialized agents
mcp__flow-nexus__agent_spawn({ type: "coordinator", name: "Project Manager" })
mcp__flow-nexus__agent_spawn({ type: "coder", name: "Backend Developer" })
mcp__flow-nexus__agent_spawn({ type: "coder", name: "Frontend Developer" })
mcp__flow-nexus__agent_spawn({ type: "coder", name: "Database Architect" })
mcp__flow-nexus__agent_spawn({ type: "analyst", name: "QA Engineer" })
 
// 3. Create development workflow
mcp__flow-nexus__workflow_create({
  name: "Full-Stack Development",
  steps: [
    { id: "requirements", action: "analyze_requirements", agent: "coordinator" },
    { id: "db_design", action: "design_schema", agent: "Database Architect" },
    { id: "backend", action: "build_api", agent: "Backend Developer", depends_on: ["db_design"] },
    { id: "frontend", action: "build_ui", agent: "Frontend Developer", depends_on: ["requirements"] },
    { id: "integration", action: "integrate", agent: "Backend Developer", depends_on: ["backend", "frontend"] },
    { id: "testing", action: "qa_testing", agent: "QA Engineer", depends_on: ["integration"] }
  ]
})
 
// 4. Execute workflow
mcp__flow-nexus__workflow_execute({
  workflow_id: "workflow_id",
  input_data: {
    project: "E-commerce Platform",
    tech_stack: ["Node.js", "React", "PostgreSQL"]
  }
})

// 1. Initialize mesh topology for collaborative research
mcp__flow-nexus__swarm_init({
  topology: "mesh",
  maxAgents: 5,
  strategy: "balanced"
})
 
// 2. Spawn research agents
mcp__flow-nexus__agent_spawn({ type: "researcher", name: "Primary Researcher" })
mcp__flow-nexus__agent_spawn({ type: "researcher", name: "Secondary Researcher" })
mcp__flow-nexus__agent_spawn({ type: "analyst", name: "Data Analyst" })
mcp__flow-nexus__agent_spawn({ type: "analyst", name: "Insights Analyst" })
 
// 3. Orchestrate research task
mcp__flow-nexus__task_orchestrate({
  task: "Research machine learning trends for 2025 and analyze market opportunities",
  strategy: "parallel",
  maxAgents: 4,
  priority: "high"
})

mcp__flow-nexus__workflow_create({
  name: "Deployment Pipeline",
  description: "Automated testing, building, and multi-environment deployment",
  steps: [
    { id: "lint", action: "lint_code", agent: "code_quality", parallel: true },
    { id: "unit_test", action: "unit_tests", agent: "test_runner", parallel: true },
    { id: "integration_test", action: "integration_tests", agent: "test_runner", parallel: true },
    { id: "build", action: "build_artifacts", agent: "builder", depends_on: ["lint", "unit_test", "integration_test"] },
    { id: "security_scan", action: "security_scan", agent: "security", depends_on: ["build"] },
    { id: "deploy_staging", action: "deploy", agent: "deployer", depends_on: ["security_scan"] },
    { id: "smoke_test", action: "smoke_tests", agent: "test_runner", depends_on: ["deploy_staging"] },
    { id: "deploy_prod", action: "deploy", agent: "deployer", depends_on: ["smoke_test"] }
  ],
  triggers: ["github_push", "github_pr_merged"],
  metadata: {
    priority: 10,
    auto_rollback: true
  }
})

mcp__flow-nexus__workflow_create({
  name: "ETL Pipeline",
  description: "Extract, Transform, Load data processing",
  steps: [
    { id: "extract", action: "extract_data", agent: "data_extractor" },
    { id: "validate_raw", action: "validate_data", agent: "validator", depends_on: ["extract"] },
    { id: "transform", action: "transform_data", agent: "transformer", depends_on: ["validate_raw"] },
    { id: "enrich", action: "enrich_data", agent: "enricher", depends_on: ["transform"] },
    { id: "load", action: "load_data", agent: "loader", depends_on: ["enrich"] },
    { id: "validate_final", action: "validate_data", agent: "validator", depends_on: ["load"] }
  ],
  triggers: ["schedule:0 2 * * *"], // Daily at 2 AM
  metadata: {
    retry_policy: "exponential_backoff",
    max_retries: 3
  }
})

// Create swarm from template
mcp__flow-nexus__swarm_create_from_template({
  template_name: "full-stack-dev",
  overrides: {
    maxAgents: 6,
    strategy: "specialized"
  }
})
 
// List available templates
mcp__flow-nexus__swarm_templates_list({
  category: "quickstart", // Options: quickstart, specialized, enterprise, custom, all
  includeStore: true
})

// Subscribe to execution streams
mcp__flow-nexus__execution_stream_subscribe({
  stream_type: "claude-flow-swarm",
  deployment_id: "deployment_id"
})
 
// Get execution status
mcp__flow-nexus__execution_stream_status({
  stream_id: "stream_id"
})
 
// List files created during execution
mcp__flow-nexus__execution_files_list({
  stream_id: "stream_id",
  created_by: "claude-flow"
})

// Get swarm performance metrics
mcp__flow-nexus__swarm_status({
  swarm_id: "id"
})
 
// Analyze workflow efficiency
mcp__flow-nexus__workflow_status({
  workflow_id: "id",
  include_metrics: true
})

// Phase 1: Research swarm
const researchSwarm = await mcp__flow-nexus__swarm_init({
  topology: "mesh",
  maxAgents: 4
})
 
// Phase 2: Development swarm
const devSwarm = await mcp__flow-nexus__swarm_init({
  topology: "hierarchical",
  maxAgents: 8
})
 
// Phase 3: Testing swarm
const testSwarm = await mcp__flow-nexus__swarm_init({
  topology: "star",
  maxAgents: 5
})

// Simple projects: Star
mcp__flow-nexus__swarm_init({ topology: "star", maxAgents: 3 })
 
// Collaborative work: Mesh
mcp__flow-nexus__swarm_init({ topology: "mesh", maxAgents: 5 })
 
// Complex projects: Hierarchical
mcp__flow-nexus__swarm_init({ topology: "hierarchical", maxAgents: 10 })
 
// Sequential workflows: Ring
mcp__flow-nexus__swarm_init({ topology: "ring", maxAgents: 4 })

// Use vector similarity for optimal matching
mcp__flow-nexus__workflow_agent_assign({
  task_id: "complex-task",
  use_vector_similarity: true
})

mcp__flow-nexus__workflow_create({
  name: "Resilient Workflow",
  steps: [...],
  metadata: {
    retry_policy: "exponential_backoff",
    max_retries: 3,
    timeout: 300000, // 5 minutes
    on_failure: "notify_and_rollback"
  }
})

// Regular monitoring
const status = await mcp__flow-nexus__swarm_status()
 
// Scale based on workload
if (status.workload > 0.8) {
  await mcp__flow-nexus__swarm_scale({ target_agents: status.agents + 2 })
}

// Long-running workflows should use message queues
mcp__flow-nexus__workflow_execute({
  workflow_id: "data-pipeline",
  async: true // Non-blocking execution
})
 
// Monitor progress
mcp__flow-nexus__workflow_queue_status({ include_messages: true })

// Destroy swarm when complete
mcp__flow-nexus__swarm_destroy({ swarm_id: "id" })

// Use proven templates instead of building from scratch
mcp__flow-nexus__swarm_create_from_template({
  template_name: "code-review",
  overrides: { maxAgents: 4 }
})

# Pre-task coordination setup
npx claude-flow@alpha hooks pre-task --description "Initialize swarm"
 
# Post-task metrics export
npx claude-flow@alpha hooks post-task --task-id "swarm-execution"

# Install Flow Nexus
npm install -g flow-nexus@latest
 
# Register account
npx flow-nexus@latest register
 
# Login
npx flow-nexus@latest login
 
# Add MCP server to Claude Code
claude mcp add flow-nexus npx flow-nexus@latest mcp start