Building GraphQL Server

Overview

Build production-ready GraphQL servers with SDL-first or code-first schema design, efficient resolver implementations with DataLoader batching, real-time subscriptions via WebSocket, and field-level authorization. Support Apollo Server, Yoga, Mercurius, and Strawberry across Node.js and Python runtimes.

Prerequisites

• Node.js 18+ with Apollo Server/Yoga/Mercurius, or Python 3.10+ with Strawberry/Ariadne
• Database with ORM (Prisma, TypeORM, SQLAlchemy) for resolver data sources
• Redis for subscription pub/sub and DataLoader caching (production deployments)
• GraphQL client for testing: GraphiQL, Apollo Studio, or Insomnia
• graphql-codegen for TypeScript type generation from schema (recommended)

Instructions

1. Examine existing data models, database schemas, and business requirements using Read and Glob to determine the entity graph and relationship structure.
2. Design the GraphQL schema with type definitions, including Query, Mutation, and Subscription root types, input types for mutations, and connection types for paginated lists.
3. Implement resolvers for each field, using DataLoader to batch and deduplicate database queries for nested relationships (N+1 query prevention).
4. Add input validation on mutation arguments using custom scalars (DateTime, Email, URL) and directive-based validation (@constraint(minLength: 1, maxLength: 255)).
5. Implement field-level authorization using schema directives (@auth(requires: ADMIN)) or resolver middleware that checks user roles from the GraphQL context.
6. Configure query complexity analysis and depth limiting to prevent abusive queries (maximum depth of 7, maximum complexity score of 1000).
7. Set up real-time subscriptions using graphql-ws protocol over WebSocket with Redis pub/sub for multi-instance message distribution.
8. Generate TypeScript types from the schema using graphql-codegen to ensure type safety between schema definitions and resolver implementations.
9. Write integration tests using executeOperation for query/mutation testing and WebSocket client tests for subscription verification.

See ${CLAUDE_SKILL_DIR}/references/implementation.md for the full implementation guide.

Output

• ${CLAUDE_SKILL_DIR}/src/schema/ - GraphQL SDL type definitions organized by domain
• ${CLAUDE_SKILL_DIR}/src/resolvers/ - Resolver implementations per type with DataLoader integration
• ${CLAUDE_SKILL_DIR}/src/dataloaders/ - DataLoader factories for batched database queries
• ${CLAUDE_SKILL_DIR}/src/directives/ - Custom schema directives (auth, validation, caching)
• ${CLAUDE_SKILL_DIR}/src/scalars/ - Custom scalar type definitions (DateTime, JSON, Email)
• ${CLAUDE_SKILL_DIR}/src/subscriptions/ - Subscription resolvers with pub/sub configuration
• ${CLAUDE_SKILL_DIR}/generated/types.ts - Auto-generated TypeScript types from schema

Error Handling

Refer to ${CLAUDE_SKILL_DIR}/references/errors.md for comprehensive error patterns.

Examples

E-commerce product catalog: Schema with Product, Category, Review types, DataLoader-backed resolvers for nested queries like products { reviews { author } }, and a productUpdated subscription for inventory changes.

Multi-tenant SaaS dashboard: Code-first schema using TypeGraphQL decorators, tenant-scoped resolvers extracting tenantId from JWT context, and field-level visibility based on subscription plan tier.

Federated microservice graph: Apollo Federation with @key and @external directives across User, Order, and Product subgraphs, composed into a unified supergraph with a gateway router.

See ${CLAUDE_SKILL_DIR}/references/examples.md for additional examples.

Resources

• GraphQL Specification: https://spec.graphql.org/
• Apollo Server documentation: https://www.apollographql.com/docs/apollo-server/
• DataLoader pattern: https://github.com/graphql/dataloader
• graphql-ws protocol: https://github.com/enisdenjo/graphql-ws