# Katana MCP Server - Comprehensive Architecture Design

**Date**: 2025-10-29 **Version**: 1.0 **Status**: Reference Document

> **⚠️ CURRENT IMPLEMENTATION**: This document provides comprehensive background on MCP
> best practices and architectural patterns. For the **current implementation plan**,
> see [MCP_V0.1.0_IMPLEMENTATION_PLAN.md](MCP_V0.1.0_IMPLEMENTATION_PLAN.md).

______________________________________________________________________

## Table of Contents

1. [Executive Summary](#executive-summary)
1. [MCP Primitives & Best Practices](#mcp-primitives--best-practices)
1. [Katana API Capabilities](#katana-api-capabilities)
1. [Proposed MCP Architecture](#proposed-mcp-architecture)
1. [Tools Design](#tools-design)
1. [Resources Design](#resources-design)
1. [Prompts Design](#prompts-design)
1. [Security & Production Readiness](#security--production-readiness)
1. [Implementation Phases](#implementation-phases)
1. [Success Metrics](#success-metrics)

______________________________________________________________________

## Executive Summary

This document outlines a comprehensive redesign of the Katana MCP server based on:

- **2025 MCP best practices** from the official specification
- **Modern architectural patterns** for production MCP servers
- **Deep understanding** of Katana Manufacturing ERP capabilities
- **Real-world manufacturing workflows** and use cases

### Key Design Principles

1. **Single Responsibility**: One MCP server focused on Katana ERP
1. **Defense in Depth**: Layered security with validation and sanitization
1. **Fail-Safe Design**: Graceful degradation under failure
1. **Production Excellence**: Observability, monitoring, health checks
1. **User-Centric**: Design around actual manufacturing workflows

______________________________________________________________________

## MCP Primitives & Best Practices

### Available MCP Features

| Primitive       | Purpose                       | When to Use                                         |
| --------------- | ----------------------------- | --------------------------------------------------- |
| **Tools**       | Functions AI can execute      | Actions, computations, external system interactions |
| **Resources**   | Context/data for AI           | Expose existing information, documents, datasets    |
| **Prompts**     | Templated workflows           | Guide user interactions, common patterns            |
| **Sampling**    | Server-initiated LLM requests | Autonomous workflows, multi-step reasoning          |
| **Roots**       | URI/filesystem boundaries     | Data source/location discovery                      |
| **Elicitation** | Request user input            | Clarification, confirmation, additional data        |

### 2025 Best Practices (from modelcontextprotocol.info)

#### Architecture

- ✅ **Single Responsibility** - One clear purpose per server
- ✅ **Defense in Depth** - Network isolation, auth, authorization, validation
- ✅ **Fail-Safe Design** - Circuit breakers, caching, rate limiting, safe defaults

#### Implementation

- ✅ **Configuration Management** - Environment variables, validation, secrets
- ✅ **Comprehensive Error Handling** - 4xx client, 5xx server, external errors
- ✅ **Performance Optimization** - Connection pooling, multi-level caching, async

#### Production Operations

- ✅ **Monitoring & Observability** - Structured logging, metrics, tracing
- ✅ **Health Checks** - Database, cache, APIs, disk, memory
- ✅ **Deployment Strategies** - Rolling updates, resource limits, autoscaling

### Performance Targets (from best practices)

| Metric       | Target                     |
| ------------ | -------------------------- |
| Throughput   | >1000 req/sec per instance |
| P95 Latency  | \<100ms (simple ops)       |
| P99 Latency  | \<500ms (complex ops)      |
| Error Rate   | \<0.1%                     |
| Availability | >99.9%                     |

______________________________________________________________________

## Katana API Capabilities

### Core Domains (52 API endpoints organized)

#### 1. **Catalog Management** (Products, Materials, Services)

- Products (finished goods): 8 endpoints
- Materials (raw materials): 8 endpoints
- Services (external): 8 endpoints
- Variants (SKU-level): 8 endpoints
- BOMs (recipes): 7 endpoints

#### 2. **Inventory Operations**

- Inventory levels: 7 endpoints
- Stock adjustments: 6 endpoints
- Stock transfers: 7 endpoints
- Stocktakes (counts): 6 endpoints
- Batches & serial numbers: 10 endpoints
- Storage bins & locations: 9 endpoints

#### 3. **Order Management**

- Sales orders: 9 endpoints
- Purchase orders: 8 endpoints
- Manufacturing orders: 10 endpoints
- Sales returns: 8 endpoints
- Order fulfillments: 7 endpoints

#### 4. **Business Relations**

- Customers: 6 endpoints
- Suppliers: 6 endpoints
- Addresses: 12 endpoints

#### 5. **Configuration & Admin**

- Price lists: 22 endpoints
- Tax rates: 4 endpoints
- Custom fields: 3 endpoints
- Webhooks: 8 endpoints
- Users: 3 endpoints
- Factories & locations: 8 endpoints

### Manufacturing Workflow Patterns

```
┌────────────────────────────────────────────────────────────────┐
│                    MANUFACTURING WORKFLOW                       │
└────────────────────────────────────────────────────────────────┘

1. CATALOG SETUP
   ├─ Create products with variants
   ├─ Define materials and BOMs
   └─ Set up suppliers and pricing

2. SALES PROCESS
   ├─ Receive sales order
   ├─ Check inventory availability
   ├─ Create manufacturing orders if needed
   └─ Fulfill and ship

3. PROCUREMENT
   ├─ Monitor low stock
   ├─ Create purchase orders
   ├─ Receive and inspect goods
   └─ Update inventory

4. PRODUCTION
   ├─ Schedule manufacturing orders
   ├─ Allocate materials
   ├─ Track production progress
   ├─ Perform quality checks
   └─ Complete and stock finished goods

5. INVENTORY MANAGEMENT
   ├─ Track stock levels
   ├─ Perform stock counts
   ├─ Transfer between locations
   └─ Adjust for discrepancies
```

______________________________________________________________________

## Proposed MCP Architecture

### High-Level Structure

```
┌─────────────────────────────────────────────────────────────┐
│                    KATANA MCP SERVER                         │
├─────────────────────────────────────────────────────────────┤
│                                                              │
│  ┌──────────────┐  ┌──────────────┐  ┌──────────────┐      │
│  │    TOOLS     │  │  RESOURCES   │  │   PROMPTS    │      │
│  │              │  │              │  │              │      │
│  │ • Inventory  │  │ • Dashboard  │  │ • Workflows  │      │
│  │ • Orders     │  │ • Reports    │  │ • Templates  │      │
│  │ • Production │  │ • Analytics  │  │ • Guides     │      │
│  │ • Catalog    │  │ • Insights   │  │              │      │
│  └──────────────┘  └──────────────┘  └──────────────┘      │
│                                                              │
├─────────────────────────────────────────────────────────────┤
│                   DOMAIN MODELS LAYER                        │
│  KatanaVariant • KatanaProduct • KatanaMaterial             │
│  KatanaSalesOrder • KatanaPurchaseOrder • KatanaMO          │
├─────────────────────────────────────────────────────────────┤
│                   RESILIENT CLIENT                           │
│  • Automatic retries  • Rate limiting  • Pagination         │
│  • Circuit breakers   • Caching        • Error handling     │
├─────────────────────────────────────────────────────────────┤
│                   KATANA API (76+ endpoints)                 │
└─────────────────────────────────────────────────────────────┘
```

### Tool Categories (20-25 tools total)

#### A. Inventory & Catalog (7-8 tools)

1. `search_products` - Find products/materials/services
1. `get_variant_details` - Get full variant info with stock
1. `check_stock_levels` - Check availability across locations
1. `list_low_stock` - Find items needing reorder
1. `adjust_stock` - Manual stock adjustments
1. `transfer_stock` - Move between locations
1. `search_batches` - Find by batch/serial numbers
1. `get_bom` - Get recipe/bill of materials

#### B. Sales Orders (5-6 tools)

1. `create_sales_order` - New customer order
1. `get_sales_order` - Retrieve order details
1. `list_sales_orders` - Find orders (filtered)
1. `update_sales_order_status` - Change status
1. `fulfill_sales_order` - Mark as shipped
1. `create_sales_return` - Handle returns

#### C. Purchase Orders (4-5 tools)

1. `create_purchase_order` - Order from supplier
1. `get_purchase_order` - Retrieve PO details
1. `list_purchase_orders` - Find POs (filtered)
1. `receive_purchase_order` - Goods receipt
1. `update_purchase_order` - Modify existing PO

#### D. Manufacturing Orders (4-5 tools)

1. `create_manufacturing_order` - Schedule production
1. `get_manufacturing_order` - Retrieve MO details
1. `list_manufacturing_orders` - Find MOs (filtered)
1. `start_manufacturing_order` - Begin production
1. `complete_manufacturing_order` - Finish and stock

#### E. Business Relations (2-3 tools)

1. `search_customers` - Find customer records
1. `search_suppliers` - Find supplier records
1. `get_customer_orders` - Order history

### Resource Categories (5-7 resources)

Resources expose **read-only data** for context.

#### A. Dashboard Resources

1. `katana://dashboard/inventory` - Current inventory summary
1. `katana://dashboard/orders` - Active orders overview
1. `katana://dashboard/production` - Manufacturing status

#### B. Report Resources

1. `katana://reports/low-stock` - Items below threshold
1. `katana://reports/overdue-orders` - Late orders
1. `katana://reports/production-schedule` - Upcoming MOs

#### C. Analytics Resources

1. `katana://analytics/turnover` - Inventory turnover rates
1. `katana://analytics/lead-times` - Supplier performance

### Prompt Categories (8-12 prompts)

Prompts provide **templated workflows** for common tasks.

#### A. Inventory Management

1. `inventory_check` - "Check stock and suggest reorders"
1. `receive_shipment` - "Process incoming goods"
1. `cycle_count` - "Perform stock count"

#### B. Order Processing

1. `new_sales_order` - "Create and validate new order"
1. `fulfill_order` - "Pick, pack, ship workflow"
1. `rush_order` - "Expedite production for urgent order"

#### C. Production Planning

1. `plan_production` - "Schedule MOs based on demand"
1. `material_requirements` - "Calculate material needs"
1. `production_start` - "Begin manufacturing process"

#### D. Troubleshooting

1. `investigate_shortage` - "Find cause of stock discrepancy"
1. `late_order_analysis` - "Diagnose delays"
1. `quality_issue` - "Handle production defect"

______________________________________________________________________

## Tools Design

### Design Principles for Tools

1. **Clear Single Purpose** - Each tool does one thing well
1. **Strict Input Validation** - JSON schema with field validation
1. **Comprehensive Error Handling** - Client/server/external errors
1. **Idempotency** - Safe to retry (where possible)
1. **Explicit Confirmation** - For state-changing operations
1. **Informative Responses** - Include context for next steps

### Tool Template Structure

```python
class ToolRequest(BaseModel):
    """Strictly validated input schema."""
    field: str = Field(..., description="Clear description", min_length=1)

class ToolResponse(BaseModel):
    """Structured, informative output."""
    result: ResultType
    metadata: dict[str, Any] = Field(default_factory=dict)  # Context
    next_actions: list[str] = Field(default_factory=list)   # Suggestions

async def tool_impl(request: ToolRequest, context: Context) -> ToolResponse:
    """Implementation with error handling and logging."""
    logger.info("tool_started", **request.dict())

    try:
        # Input validation
        if not request.field:
            raise ValueError("Field required")

        # Business logic
        client = context.request_context.lifespan_context.client
        result = await client.domain.operation(request.field)

        # Success logging
        logger.info("tool_completed", result_count=len(result))

        return ToolResponse(
            result=result,
            metadata={"source": "katana_api"},
            next_actions=["Check result", "Take next step"]
        )

    except ValueError as e:
        # Client error (4xx)
        logger.warning("tool_validation_failed", error=str(e))
        raise
    except Exception as e:
        # Server error (5xx)
        logger.error("tool_failed", error=str(e), exc_info=True)
        raise
```

### Example: Create Sales Order Tool (Enhanced)

```python
class CreateSalesOrderRequest(BaseModel):
    """Request to create a new sales order."""
    customer_id: int = Field(..., description="Customer ID", gt=0)
    items: list[OrderItem] = Field(..., description="Order line items", min_items=1)
    notes: str | None = Field(None, description="Optional order notes")
    priority: Literal["normal", "high", "urgent"] = Field("normal")
    requested_delivery_date: date | None = None

    # Elicitation: Ask for confirmation before creating
    confirm: bool = Field(
        False,
        description="Set to true to confirm order creation"
    )

class OrderItem(BaseModel):
    """Line item in sales order."""
    variant_id: int = Field(..., gt=0)
    quantity: float = Field(..., gt=0)
    unit_price: float | None = None  # Auto-fill from price list

class CreateSalesOrderResponse(BaseModel):
    """Response with created order details."""
    order_id: int
    order_number: str
    total_amount: float
    estimated_delivery: date | None
    manufacturing_required: bool
    warnings: list[str] = Field(default_factory=list)
    next_actions: list[str] = Field(default_factory=list)

async def create_sales_order(
    request: CreateSalesOrderRequest,
    context: Context
) -> CreateSalesOrderResponse:
    """Create a new sales order with validation and confirmation.

    This tool implements best practices:
    - Input validation (customer exists, items valid)
    - Stock availability check
    - Automatic pricing from price lists
    - Manufacturing requirement detection
    - Explicit confirmation for creation
    - Informative warnings and next actions
    """
    logger.info("create_sales_order_started", customer_id=request.customer_id)

    client = context.request_context.lifespan_context.client

    # 1. Validate customer exists
    customer = await client.customers.get(request.customer_id)
    if not customer:
        raise ValueError(f"Customer {request.customer_id} not found")

    # 2. Validate items and check stock
    warnings = []
    for item in request.items:
        variant = await client.variants.get(item.variant_id)
        if not variant:
            raise ValueError(f"Variant {item.variant_id} not found")

        # Check stock availability
        stock = await client.inventory.check_stock(variant.sku)
        if stock.available < item.quantity:
            warnings.append(
                f"Insufficient stock for {variant.sku}: "
                f"need {item.quantity}, have {stock.available}"
            )

    # 3. Elicitation: Require confirmation if not provided
    if not request.confirm:
        # Return preview without creating
        return CreateSalesOrderResponse(
            order_id=0,  # Not created yet
            order_number="PREVIEW",
            total_amount=0.0,  # Calculate preview
            estimated_delivery=request.requested_delivery_date,
            manufacturing_required=len(warnings) > 0,
            warnings=warnings + [
                "⚠️ Order not created. Set confirm=true to create."
            ],
            next_actions=[
                "Review warnings",
                "Set confirm=true to proceed",
                "Or adjust quantities"
            ]
        )

    # 4. Create order
    order = await client.sales_orders.create(
        customer_id=request.customer_id,
        items=[{
            "variant_id": item.variant_id,
            "quantity": item.quantity,
        } for item in request.items],
        notes=request.notes,
    )

    logger.info("sales_order_created", order_id=order.id)

    return CreateSalesOrderResponse(
        order_id=order.id,
        order_number=order.order_number,
        total_amount=order.total_amount,
        estimated_delivery=order.estimated_delivery,
        manufacturing_required=len(warnings) > 0,
        warnings=warnings,
        next_actions=[
            f"View order: get_sales_order(order_id={order.id})",
            "Create manufacturing orders if needed",
            "Process payment",
        ]
    )
```

______________________________________________________________________

## Resources Design

Resources expose **read-only contextual data** that LLMs can reference.

### Design Principles

1. **URI-based addressing** - `katana://domain/resource`
1. **Cached & efficient** - Don't hit API on every access
1. **Structured data** - JSON/YAML for easy parsing
1. **Time-bounded** - Include timestamps, refresh info
1. **Actionable** - Link to relevant tools

### Example: Inventory Dashboard Resource

```python
@mcp.resource("katana://dashboard/inventory")
async def inventory_dashboard(context: Context) -> Resource:
    """Current inventory status dashboard.

    Provides:
    - Total SKU count
    - Low stock items (< threshold)
    - Out of stock items
    - Top movers (by turnover)
    - Slow movers
    - Stock value

    Refreshes: Every 5 minutes
    """
    client = context.request_context.lifespan_context.client

    # Get cached dashboard data
    dashboard = await client.inventory.get_dashboard(cache_ttl=300)

    return Resource(
        uri="katana://dashboard/inventory",
        mimeType="application/json",
        text=json.dumps({
            "generated_at": datetime.now().isoformat(),
            "next_refresh": (datetime.now() + timedelta(minutes=5)).isoformat(),
            "summary": {
                "total_skus": dashboard.total_skus,
                "total_value": dashboard.total_value,
                "low_stock_count": len(dashboard.low_stock),
                "out_of_stock_count": len(dashboard.out_of_stock),
            },
            "low_stock_items": [
                {
                    "sku": item.sku,
                    "name": item.name,
                    "current": item.current_stock,
                    "threshold": item.reorder_point,
                    "suggested_order_qty": item.economic_order_quantity,
                }
                for item in dashboard.low_stock[:10]
            ],
            "out_of_stock": [
                {"sku": item.sku, "name": item.name}
                for item in dashboard.out_of_stock[:10]
            ],
            "next_actions": [
                "Review low stock items",
                "Use list_low_stock tool for full list",
                "Create purchase orders for critical items",
            ]
        }, indent=2)
    )
```

______________________________________________________________________

## Prompts Design

Prompts guide users through **common workflows** with structured templates.

### Design Principles

1. **Workflow-oriented** - Match real business processes
1. **Step-by-step** - Clear progression
1. **Context-aware** - Reference current state
1. **Interactive** - Elicit clarifications
1. **Tool-integrated** - Call appropriate tools

### Example: Fulfill Sales Order Workflow

```python
@mcp.prompt("fulfill_order")
async def fulfill_order_prompt(context: Context, order_id: int) -> Prompt:
    """Guide user through order fulfillment process.

    Workflow:
    1. Retrieve order details
    2. Check inventory availability
    3. Allocate stock
    4. Generate pick list
    5. Confirm picking
    6. Generate packing slip
    7. Confirm shipping
    8. Update order status
    """
    return Prompt(
        name="fulfill_order",
        description=f"Fulfill sales order #{order_id}",
        messages=[
            PromptMessage(
                role="user",
                content=f"""I need to fulfill sales order #{order_id}.

Please help me through the process:

1. First, show me the order details and check if we have sufficient stock
2. If stock is available, generate a pick list
3. After I confirm picking, generate a packing slip
4. Finally, mark the order as shipped

Let's start by retrieving the order."""
            ),
            PromptMessage(
                role="assistant",
                content=f"""I'll help you fulfill order #{order_id}. Let me start by retrieving the order details and checking stock availability.

{{% call_tool name="get_sales_order" args={{"order_id": {order_id}}} %}}"""
            )
        ]
    )
```

______________________________________________________________________

## Security & Production Readiness

### Security Layers

#### 1. Network Isolation

```python
# Bind to localhost only
server.bind("127.0.0.1", 8080)
```

#### 2. Authentication

```python
# API key from environment
api_key = os.getenv("KATANA_API_KEY")
if not api_key:
    raise ValueError("KATANA_API_KEY required")
```

#### 3. Authorization

```python
# Tool-level permissions (future)
@mcp.tool(requires_permission="inventory:write")
async def adjust_stock(...):
    pass
```

#### 4. Input Validation

```python
# Pydantic strict mode
class StrictRequest(BaseModel):
    class Config:
        extra = "forbid"  # Reject unknown fields
        str_strip_whitespace = True
        min_anystr_length = 1
```

#### 5. Output Sanitization

```python
# Remove sensitive data
def sanitize_response(data: dict) -> dict:
    """Remove API keys, internal IDs, etc."""
    return {
        k: v for k, v in data.items()
        if k not in ["api_key", "internal_id"]
    }
```

#### 6. Monitoring

```python
# Structured logging with security events
logger.warning(
    "unauthorized_access_attempt",
    user=user_id,
    resource=resource_name,
    ip=request.ip
)
```

### Production Checklist

#### Phase 1: Core Compliance

- [ ] All tools have input validation
- [ ] All tools have error handling
- [ ] All tools have structured logging
- [ ] Health check endpoint implemented
- [ ] Configuration validated at startup

#### Phase 2: Security

- [ ] Network isolation configured
- [ ] API key validation
- [ ] Input sanitization
- [ ] Output sanitization
- [ ] Rate limiting per client

#### Phase 3: Performance

- [ ] Connection pooling (5-20 connections)
- [ ] Multi-level caching (memory, Redis)
- [ ] Async processing for long operations
- [ ] Resource limits configured

#### Phase 4: Observability

- [ ] Prometheus metrics exported
- [ ] Structured JSON logging
- [ ] Request tracing with trace IDs
- [ ] Error alerting configured
- [ ] Performance dashboards

#### Phase 5: Reliability

- [ ] Circuit breakers on external calls
- [ ] Graceful degradation modes
- [ ] Health checks for dependencies
- [ ] Rolling deployment strategy
- [ ] Horizontal autoscaling

______________________________________________________________________

## Implementation Phases

### Phase 1: Foundation (Week 1-2)

**Goal**: Core tools with production patterns

#### Deliverables

- [ ] Enhanced inventory tools (3 tools)
  - `search_products` - With caching, ranking
  - `check_stock_levels` - Multi-location support
  - `list_low_stock` - With reorder suggestions
- [ ] Structured logging system
- [ ] Health check endpoint
- [ ] Input validation patterns
- [ ] Error handling framework

#### Success Criteria

- All tools have comprehensive error handling
- Structured logs capture key events
- P95 latency < 100ms

### Phase 2: Core Tools (Week 3-4)

**Goal**: Essential order management

#### Deliverables

- [ ] Sales order tools (4 tools)
  - Create, get, list, fulfill
- [ ] Purchase order tools (3 tools)
  - Create, get, receive
- [ ] Manufacturing order tools (3 tools)
  - Create, get, list
- [ ] Elicitation for confirmations
- [ ] Response metadata & next actions

#### Success Criteria

- End-to-end order workflows functional
- Confirmation required for state changes
- All tools return actionable next steps

### Phase 3: Resources & Prompts (Week 5)

**Goal**: Context and guided workflows

#### Deliverables

- [ ] Dashboard resources (3 resources)
  - Inventory, orders, production
- [ ] Report resources (2 resources)
  - Low stock, overdue orders
- [ ] Workflow prompts (5 prompts)
  - New order, fulfillment, production
- [ ] Resource caching layer
- [ ] Prompt templates

#### Success Criteria

- Resources refresh efficiently (\<1s)
- Prompts guide complete workflows
- Users can complete tasks without API knowledge

### Phase 4: Advanced Features (Week 6-7)

**Goal**: Production excellence

#### Deliverables

- [ ] Advanced inventory tools
  - Stock transfers, adjustments, batch tracking
- [ ] Analytics resources
  - Turnover, lead times
- [ ] Troubleshooting prompts
  - Shortage investigation, late orders
- [ ] Performance optimization
  - Connection pooling, caching
- [ ] Monitoring & alerting

#### Success Criteria

- > 1000 req/sec throughput
- \<0.1% error rate
- Full observability stack

### Phase 5: Polish & Documentation (Week 8)

**Goal**: Production ready

#### Deliverables

- [ ] Comprehensive documentation
- [ ] Usage examples
- [ ] Integration tests
- [ ] Load testing results
- [ ] Security audit
- [ ] Deployment guide

#### Success Criteria

- 99.9% availability in staging
- All use cases documented
- Security review passed

______________________________________________________________________

## Success Metrics

### User Experience Metrics

| Metric                 | Target   | Rationale                                 |
| ---------------------- | -------- | ----------------------------------------- |
| Task Completion Rate   | >90%     | Users successfully complete workflows     |
| Time to Complete Order | \<2 min  | From order creation to confirmation       |
| Error Recovery Rate    | >95%     | Users recover from errors without support |
| Tool Discovery Time    | \<30 sec | Users find the right tool quickly         |

### Technical Metrics

| Metric                | Target  | Rationale            |
| --------------------- | ------- | -------------------- |
| API Call Success Rate | >99.5%  | Including retries    |
| P95 Response Time     | \<100ms | Simple operations    |
| P99 Response Time     | \<500ms | Complex operations   |
| Cache Hit Rate        | >80%    | For frequent queries |
| Availability          | >99.9%  | Production uptime    |

### Business Metrics

| Metric               | Target   | Rationale                   |
| -------------------- | -------- | --------------------------- |
| Orders Processed/Day | Baseline | Track adoption              |
| Automation Rate      | >50%     | LLM completes without human |
| Support Tickets      | \<5/week | Measure usability           |
| User Satisfaction    | >4.5/5   | NPS survey                  |

______________________________________________________________________

## Conclusion

This architecture provides:

1. **Comprehensive Coverage** - 20-25 tools covering all major workflows
1. **Production Ready** - Security, observability, performance
1. **User Friendly** - Prompts, resources, clear documentation
1. **Maintainable** - Clean patterns, single responsibility
1. **Scalable** - Connection pooling, caching, autoscaling

The phased approach allows us to:

- Validate patterns early (Phase 1)
- Deliver value incrementally (Phase 2-3)
- Optimize for production (Phase 4)
- Launch confidently (Phase 5)

**Next Steps**: Review this design, get feedback, and begin Phase 1 implementation.
