moai-domain-backend

name	moai-domain-backend
description	Backend development specialist covering API design, database integration, microservices architecture, and modern backend patterns. Use when designing APIs, implementing server logic, authentication, or authorization.
when_to_use	Use for backend work: API design (REST, GraphQL, gRPC), server logic, authentication and authorization, microservices, middleware, caching, and frameworks (FastAPI, Express, Django, Flask). Covers serverless, PostgreSQL, MongoDB, and Redis integration.
license	Apache-2.0
compatibility	Designed for Claude Code
allowed-tools	Read, Write, Edit, Bash(npm:*), Bash(npx:*), Bash(node:*), Bash(uv:*), Bash(pip:*), Bash(pytest:*), Bash(ruff:*), Bash(docker:*), Bash(curl:*), Bash(go:*), Bash(cargo:*), Grep, Glob
user-invocable	false
metadata	{"version":"1.0.0","category":"domain","status":"active","updated":"2026-01-11","modularized":"false","tags":"backend, api, database, microservices, architecture","author":"MoAI-ADK Team"}

Backend Development Specialist

Quick Reference

Backend Development Mastery - Comprehensive backend development patterns covering API design, database integration, microservices, and modern architecture patterns.

Core Capabilities:

• API Design: REST, GraphQL, gRPC with OpenAPI 3.1
• Database Integration: PostgreSQL, MongoDB, Redis, caching strategies
• Microservices: Service mesh, distributed patterns, event-driven architecture
• Security: Authentication, authorization, OWASP compliance
• Performance: Caching, optimization, monitoring, scaling

When to Use:

• Backend API development and architecture
• Database design and optimization
• Microservices implementation
• Performance optimization and scaling
• Security integration for backend systems

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Implementation Guide

API Design Patterns

RESTful API Architecture:

Create a FastAPI application with authentication and response models. Define a Pydantic UserResponse model with id, email, and name fields. Implement list_users and create_user endpoints with HTTPBearer security dependency. The list endpoint returns a list of UserResponse objects, while the create endpoint accepts a UserCreate model and returns a single UserResponse.

GraphQL Implementation:

Use Strawberry to define GraphQL types. Create a User type with id, email, and name fields. Define a Query type with a users resolver that returns a list of User objects asynchronously. Generate the schema by passing the Query type to strawberry.Schema.

Database Integration Patterns

PostgreSQL with SQLAlchemy:

Define SQLAlchemy models using declarative_base. Create a User model with id as primary key, email as unique string, and name as string column. Configure the engine with connection pooling parameters including pool_size of 20, max_overflow of 30, and pool_pre_ping enabled for connection health checks.

MongoDB with Motor:

Create a UserService class that initializes with an AsyncIOMotorClient. Set up the database and users collection in the constructor. Create indexes for email (unique) and created_at fields. Implement create_user method that inserts a document and returns the inserted_id as string.

Microservices Architecture

Service Discovery with Consul:

Create a ServiceRegistry class that connects to Consul. Implement register_service method that registers a service with name, id, port, and health check endpoint. Implement discover_service method that queries healthy services and returns list of address:port strings.

Event-Driven Architecture:

Create an EventBus class using aio_pika for AMQP messaging. Implement connect method to establish connection and channel. Implement publish_event method that serializes event type and data as JSON and publishes to the default exchange with routing_key matching the event type.