System Design¶

Overview¶

The NetApp ActiveIQ MCP Server implements a bridge between the Model Context Protocol (MCP) and NetApp's ActiveIQ Unified Manager API, enabling AI assistants and automation tools to interact with NetApp storage infrastructure through natural language interfaces.

High-Level Architecture¶

graph TB

    subgraph "AI/Client Layer"
        A1[Claude Desktop]
        A2[Custom AI App]
        A3[MCP Client]
    end

    subgraph "MCP Protocol Layer"
        B1[MCP Transport]
        B2[Tool Registry]
        B3[Schema Validator]
    end

    subgraph "NetApp MCP Server Core"
        C1[Request Router]
        C2[Tool Executor]
        C3[Response Formatter]
        C4[Authentication Manager]
        C5[Cache Manager]
        C6[Event Handler]
    end

    subgraph "Integration Layer"
        D1[NetApp API Client]
        D2[Temporal Workflows]
        D3[Prometheus Metrics]
        D4[Error Handler]
    end

    subgraph "NetApp Infrastructure"
        E1[ActiveIQ Unified Manager]
        E2[ONTAP Clusters]
        E3[Storage Systems]
    end

    subgraph "External Services"
        F1[Temporal Server]
        F2[Redis Cache]
        F3[Monitoring System]
    end

    A1 --> B1
    A2 --> B1
    A3 --> B1

    B1 --> C1
    B2 --> C2
    B3 --> C3

    C1 --> D1
    C2 --> D2
    C3 --> D3
    C4 --> D1
    C5 --> F2
    C6 --> D4

    D1 --> E1
    D2 --> F1
    D3 --> F3

    E1 --> E2
    E1 --> E3

Component Architecture¶

MCP Protocol Layer¶

MCP Transport¶

Purpose: Handles MCP protocol communication
Responsibilities:
Message serialization/deserialization
Protocol version negotiation
Connection management
Error propagation

Tool Registry¶

Purpose: Maintains registry of available MCP tools
Responsibilities:
Tool discovery and registration
Schema validation
Tool metadata management
Capability advertisement

Schema Validator¶

Purpose: Validates MCP messages and tool arguments
Responsibilities:
JSON schema validation
Type checking
Parameter validation
Error reporting

Server Core¶

Request Router¶

Purpose: Routes incoming MCP requests to appropriate handlers

Implementation:

class RequestRouter:
    def __init__(self):
        self.tools = ToolRegistry()
        self.auth = AuthenticationManager()

    async def route_request(self, request: MCPRequest) -> MCPResponse:
        # Authenticate request
        if not await self.auth.validate(request):
            return MCPResponse.error("Authentication failed")

        # Route to tool
        tool = self.tools.get_tool(request.method)
        if not tool:
            return MCPResponse.error("Tool not found")

        return await tool.execute(request.params)

Tool Executor¶

Purpose: Executes NetApp operations through registered tools
Key Features:
Async execution
Timeout handling
Rate limiting
Result caching

Response Formatter¶

Purpose: Formats responses according to MCP specification
Responsibilities:
Result serialization
Error formatting
Schema compliance
Content negotiation

Authentication Manager¶

Purpose: Manages NetApp API authentication

Implementation:

class AuthenticationManager:
    def __init__(self, config: NetAppConfig):
        self.session = aiohttp.ClientSession(
            auth=aiohttp.BasicAuth(config.username, config.password),
            connector=aiohttp.TCPConnector(ssl=config.verify_ssl)
        )

    async def validate_connection(self) -> bool:
        try:
            async with self.session.get(f"{self.base_url}/datacenter/cluster/clusters") as resp:
                return resp.status == 200
        except Exception:
            return False

Integration Layer¶

NetApp API Client¶

Purpose: Interfaces with ActiveIQ Unified Manager API
Key Features:
Connection pooling
Retry logic
Response caching
Error handling

class NetAppAPIClient:
    def __init__(self, config: NetAppConfig):
        self.base_url = f"https://{config.host}/api/v2"
        self.session = self._create_session(config)

    async def get_clusters(self, **params) -> List[Dict]:
        url = f"{self.base_url}/datacenter/cluster/clusters"
        async with self.session.get(url, params=params) as resp:
            data = await resp.json()
            return data.get('records', [])

Temporal Workflows¶

Purpose: Orchestrates complex, long-running NetApp operations
Use Cases:
SVM creation workflows
Volume provisioning
Data migration
Backup operations

Prometheus Metrics¶

Purpose: Exposes operational metrics
Metrics:
Request count and duration
NetApp API response times
Error rates
Cache hit/miss ratios

Data Flow¶

Request Processing Flow¶

sequenceDiagram
    participant Client as MCP Client
    participant Server as MCP Server
    participant Cache as Cache Layer
    participant NetApp as NetApp API

    Client->>Server: MCP Request
    Server->>Server: Validate Request
    Server->>Server: Authenticate
    Server->>Cache: Check Cache

    alt Cache Hit
        Cache-->>Server: Cached Response
    else Cache Miss
        Server->>NetApp: API Request
        NetApp-->>Server: API Response
        Server->>Cache: Store Response
    end

    Server->>Server: Format Response
    Server-->>Client: MCP Response

Error Handling Flow¶

sequenceDiagram
    participant Client as MCP Client
    participant Server as MCP Server
    participant NetApp as NetApp API
    participant Monitor as Monitoring

    Client->>Server: MCP Request
    Server->>NetApp: API Request
    NetApp-->>Server: Error Response

    Server->>Server: Parse Error
    Server->>Monitor: Log Error
    Server->>Server: Format Error Response
    Server-->>Client: MCP Error Response

Scalability Design¶

Horizontal Scaling¶

Stateless Design: Server instances are stateless
Load Balancing: Support for multiple server instances
Shared Cache: Redis for cross-instance caching
Database: External storage for persistent data

Performance Optimization¶

Connection Pooling: Reuse HTTP connections to NetApp APIs
Async Processing: Non-blocking I/O operations
Caching Strategy: Multi-level caching (memory + Redis)
Request Batching: Batch multiple requests when possible

Resource Management¶

class ResourceManager:
    def __init__(self, config: Config):
        self.semaphore = asyncio.Semaphore(config.max_concurrent_requests)
        self.connection_pool = aiohttp.TCPConnector(
            limit=config.max_connections,
            limit_per_host=config.max_connections_per_host
        )

    async def execute_with_limit(self, coro):
        async with self.semaphore:
            return await coro

Security Architecture¶

Authentication Flow¶

sequenceDiagram
    participant Client as MCP Client
    participant Server as MCP Server
    participant Auth as Auth Service
    participant NetApp as NetApp API

    Client->>Server: Request with Token
    Server->>Auth: Validate Token
    Auth-->>Server: Token Valid
    Server->>NetApp: API Request (Service Account)
    NetApp-->>Server: Response
    Server-->>Client: MCP Response

Security Layers¶

Transport Security: TLS encryption
Authentication: JWT tokens or API keys
Authorization: Role-based access control
NetApp Security: Service account with minimal permissions
Input Validation: Strict parameter validation
Output Sanitization: Sensitive data filtering

Configuration Management¶

Configuration Schema¶

# Server configuration
server:
  host: "0.0.0.0"
  port: 8080
  workers: 4
  max_connections: 100
  timeout: 30

# NetApp configuration
netapp:
  um_host: "unified-manager.company.com"
  username: "service-account"
  password: "${NETAPP_PASSWORD}"
  verify_ssl: false
  timeout: 30
  max_retries: 3

# Cache configuration
cache:
  type: "redis"
  url: "redis://localhost:6379"
  ttl: 300
  max_size: 1000

# Monitoring configuration
monitoring:
  metrics_enabled: true
  metrics_port: 9090
  health_check_interval: 30
  log_level: "INFO"

Deployment Architecture¶

Container Architecture¶

FROM python:3.11-slim

# Install dependencies
COPY requirements.txt .
RUN pip install -r requirements.txt

# Copy application
COPY . /app
WORKDIR /app

# Set up user
RUN adduser --disabled-password --gecos '' netapp
USER netapp

# Health check
HEALTHCHECK --interval=30s --timeout=10s --start-period=5s --retries=3 \
  CMD curl -f http://localhost:8080/health || exit 1

CMD ["python", "-m", "netapp_mcp_server"]

Kubernetes Deployment¶

apiVersion: apps/v1
kind: Deployment
metadata:
  name: netapp-mcp-server
spec:
  replicas: 3
  selector:
    matchLabels:
      app: netapp-mcp-server
  template:
    metadata:
      labels:
        app: netapp-mcp-server
    spec:
      containers:
      - name: netapp-mcp-server
        image: netapp/activeiq-mcp-server:latest
        ports:
        - containerPort: 8080
        env:
        - name: NETAPP_UM_HOST
          valueFrom:
            secretKeyRef:
              name: netapp-credentials
              key: um-host
        resources:
          requests:
            memory: "512Mi"
            cpu: "250m"
          limits:
            memory: "1Gi"
            cpu: "500m"
        livenessProbe:
          httpGet:
            path: /health
            port: 8080
          initialDelaySeconds: 30
          periodSeconds: 10

Monitoring and Observability¶

Metrics Collection¶

Application Metrics: Request rates, response times, error rates
System Metrics: CPU, memory, disk usage
NetApp Metrics: API response times, connection status
Business Metrics: Tool usage, user activity

Logging Strategy¶

import structlog

logger = structlog.get_logger("netapp.mcp.server")

async def execute_tool(tool_name: str, params: dict):
    logger.info("tool.execute.start", tool=tool_name, params=params)

    try:
        result = await tool.execute(params)
        logger.info("tool.execute.success", tool=tool_name, result_size=len(result))
        return result
    except Exception as e:
        logger.error("tool.execute.error", tool=tool_name, error=str(e))
        raise

Health Checks¶

class HealthChecker:
    async def check_health(self) -> Dict[str, Any]:
        checks = {
            "server": await self.check_server(),
            "netapp": await self.check_netapp_connection(),
            "cache": await self.check_cache(),
            "temporal": await self.check_temporal()
        }

        status = "healthy" if all(checks.values()) else "unhealthy"
        return {"status": status, "checks": checks}

Future Enhancements¶

Planned Features¶

GraphQL Support: Alternative query interface
WebSocket Support: Real-time event streaming
Plugin System: Extensible tool architecture
Multi-tenant Support: Isolated environments
Advanced Caching: Intelligent cache invalidation
ML Integration: Predictive analytics

Scalability Roadmap¶

Database Layer: Persistent storage for complex queries
Event Streaming: Kafka/Pulsar for event processing
Microservices: Split into specialized services
API Gateway: Centralized routing and security
Service Mesh: Advanced networking and observability