/payments

name: flow-nexus-payments
description: Credit management, billing, and payment configuration

Flow Nexus Payments

Manage credits, configure billing, and track usage.

Check Balance

mcp__flow-nexus__check_balance()

Purchase Credits

// Create payment link
mcp__flow-nexus__create_payment_link({
  amount: 50 // USD, minimum $10
})
// Returns secure payment URL to complete purchase

Auto-Refill Configuration

// Enable auto-refill
mcp__flow-nexus__configure_auto_refill({
  enabled: true,
  threshold: 100,  // Refill when credits drop below 100
  amount: 50       // Refill with $50 worth of credits
})

// Disable auto-refill
mcp__flow-nexus__configure_auto_refill({
  enabled: false
})

Payment History

mcp__flow-nexus__get_payment_history({
  limit: 50
})

rUv Credits Management

// Check balance
mcp__flow-nexus__ruv_balance({
  user_id: "your_id"
})

// Transaction history
mcp__flow-nexus__ruv_history({
  user_id: "your_id",
  limit: 100
})

Upgrade Tier

mcp__flow-nexus__user_upgrade({
  user_id: "your_id",
  tier: "pro" // pro, enterprise
})

Usage Statistics

mcp__flow-nexus__user_stats({
  user_id: "your_id"
})

Credit Pricing

• **Swarm Operations**: 1-10 credits/hour
• **Sandbox Execution**: 0.5-5 credits/hour
• **Neural Training**: 5-50 credits/job
• **Workflow Runs**: 0.1-1 credit/execution
• **Storage**: 0.01 credits/GB/day

Earning Credits

1. **Complete Challenges**: 10-500 credits per challenge 2. **Publish Templates**: Earn when others use 3. **Referrals**: Bonus credits for invites 4. **Daily Login**: Small daily bonus 5. **Achievements**: Unlock milestone rewards

Tiers

Free Tier

• 100 free credits monthly
• Basic sandbox access
• Limited swarm agents (3 max)
• Community support

Pro Tier ($29/month)

• 1000 credits monthly
• Priority sandbox access
• Unlimited agents
• Advanced workflows
• Email support

Enterprise Tier (Custom)

• Unlimited credits
• Dedicated resources
• Custom models
• SLA guarantee
• Priority support

Cost Optimization Tips

1. Use smaller sandboxes when possible 2. Optimize neural network training parameters 3. Batch workflow executions 4. Clean up unused resources 5. Monitor usage regularly 6. Use templates to avoid redundant work