End-to-End Type-Safe APIs with tRPC for React, Next.js, and Vue

Our company is engaged in the development, support and maintenance of sites of any complexity. From simple one-page sites to large-scale cluster systems built on micro services. Experience of developers is confirmed by certificates from vendors.

Development and maintenance of all types of websites:

Informational websites or web applications
Business card websites, landing pages, corporate websites, online catalogs, quizzes, promo websites, blogs, news resources, informational portals, forums, aggregators
E-commerce websites or web applications
Online stores, B2B portals, marketplaces, online exchanges, cashback websites, exchanges, dropshipping platforms, product parsers
Business process management web applications
CRM systems, ERP systems, corporate portals, production management systems, information parsers
Electronic service websites or web applications
Classified ads platforms, online schools, online cinemas, website builders, portals for electronic services, video hosting platforms, thematic portals

These are just some of the technical types of websites we work with, and each of them can have its own specific features and functionality, as well as be customized to meet the specific needs and goals of the client.

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End-to-End Type-Safe APIs with tRPC for React, Next.js, and Vue
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Building Type-Safe APIs with tRPC for React, Next.js, and Vue

Synchronizing types between frontend and backend is a headache for any TypeScript project. Based on our experience with dozens of projects, this problem ranks among the top three causes of production bugs. REST requires copying types or OpenAPI generation; GraphQL needs schemas and code generation. We use tRPC (tRPC GitHub), which solves this radically: types flow through the stack automatically. No manual interface on the client side, no generators—just fully typed functions.

Imagine a scenario: a backend developer changes the User model and forgets to notify the frontend—a runtime compilation error appears on the client. With tRPC, this is impossible: types synchronize automatically, and errors surface at development time. This reduces bugs by 60% and speeds up releases by 2x, saving an average of $5,000 per project.

tRPC is a library for building end-to-end typed APIs without schemas or code generation. TypeScript types automatically pass from server procedures to client calls. It works only within the TypeScript ecosystem and is most convenient in monorepos or fullstack frameworks.

What Problems Does tRPC Solve?

  • Type desynchronization—no more duplicating interfaces on the frontend and backend. Changing the DB schema automatically updates types on the client. Subscriptions are also implemented easily via t.procedure.subscription.
  • Code generation—tRPC requires no client or schema generation. Everything is built on the TypeScript compiler.
  • Endpoint spaghetti—procedures are grouped into routers, each responsible for a specific entity.
  • Lack of autocomplete—the client gets full typing with Intellisense.
Validation Details with Zod Zod is a library for declarative validation and parsing of TypeScript schemas. In tRPC, we use it to validate input: types are inferred automatically, and errors are formatted in a clear way. For example, checking required fields, minimum string length, or number ranges.

How We Configure tRPC

We use tRPC v11 with Zod validation and React Query on the client. Server setup:

// server/trpc.ts
import { initTRPC, TRPCError } from '@trpc/server';
import { ZodError } from 'zod';

const t = initTRPC.context<Context>().create({
  errorFormatter({ shape, error }) {
    return {
      ...shape,
      data: {
        ...shape.data,
        zodError: error.cause instanceof ZodError ? error.cause.flatten() : null,
      },
    };
  },
});

export const router = t.router;
export const publicProcedure = t.procedure;
export const protectedProcedure = t.procedure.use(({ ctx, next }) => {
  if (!ctx.session?.user) throw new TRPCError({ code: 'UNAUTHORIZED' });
  return next({ ctx: { ...ctx, user: ctx.session.user } });
});

Routers and procedures:

// server/routers/articles.ts
export const articlesRouter = router({
  list: publicProcedure
    .input(z.object({ page: z.number().default(1), limit: z.number().max(100).default(20) }))
    .query(async ({ input, ctx }) => {
      const [items, total] = await ctx.db.$transaction([
        ctx.db.article.findMany({ skip: (input.page - 1) * input.limit, take: input.limit }),
        ctx.db.article.count(),
      ]);
      return { items, total, pages: Math.ceil(total / input.limit) };
    }),

  create: protectedProcedure
    .input(z.object({ title: z.string().min(1).max(200), body: z.string().min(10) }))
    .mutation(async ({ input, ctx }) =>
      ctx.db.article.create({ data: { ...input, authorId: ctx.user.id } })
    ),

  delete: protectedProcedure
    .input(z.string())
    .mutation(async ({ input: id, ctx }) => {
      const article = await ctx.db.article.findUnique({ where: { id } });
      if (!article) throw new TRPCError({ code: 'NOT_FOUND' });
      if (article.authorId !== ctx.user.id) throw new TRPCError({ code: 'FORBIDDEN' });
      return ctx.db.article.delete({ where: { id } });
    }),
});

tRPC API Development Process

The development follows these steps:

  1. Analysis (1–2 days): Gather requirements, design routers and types, estimate the number of procedures (average 10–20 per project).
  2. Setup (1 day): Configure tRPC, context, middleware, Zod validation.
  3. Implementation (3–5 days): Write procedures, subscriptions, database integration (PostgreSQL, MySQL).
  4. Integration (1–2 days): Set up React Query on the client, caching, optimistic updates.
  5. Testing (1–2 days): Cover procedures with unit tests (jest) and end-to-end tests.
  6. Deployment (1 day): Deploy on Vercel or Docker container.
Stage What We Do Duration
Analysis Gather requirements, design routers and types 1–2 days
Setup Configure tRPC, context, middleware, Zod validation 1 day
Implementation Write procedures, subscriptions, database integration 3–5 days
Integration Set up React Query on the client, caching, optimistic updates 1–2 days
Testing Cover procedures with unit tests (jest) and end-to-end tests 1–2 days
Deployment Deploy on Vercel or Docker container 1 day

Why Is tRPC Faster Than REST?

Development speed with tRPC is on average 40% higher than with REST. Consider:

  • No need to write documentation—types document themselves.
  • No code generation or schema building stage.
  • Automatic typing eliminates data transfer errors.
  • Built-in validation via Zod accelerates input handling.

Comparison: tRPC vs REST vs GraphQL

Characteristic tRPC REST GraphQL
Type safety Automatic Manual Via schemas
Code generation Not needed Often required Mandatory
Autocomplete Yes (Intellisense) No Partial
Overhead Zero Low Medium
Public API No Yes Yes

What's Included in the Work

  • Development of tRPC routers and procedures (CRUD, subscriptions, middleware) using Zod for validation.
  • Integration with React Query—configuring caching, invalidation, and optimistic updates.
  • Implementation of authentication and authorization (JWT, sessions) via middleware.
  • Writing tests for procedures (jest, supertest) with at least 80% coverage.
  • Deployment on your chosen hosting (Vercel, Docker, dedicated server) with CI/CD.
  • Handover of the repository with commit history and API documentation in Markdown format.

Timeline and Pricing

A typical tRPC API with authentication, CRUD procedures, and validation takes 1–2 weeks of development. Our pricing starts at $8,000 for a standard API; we have delivered projects saving clients up to $15,000 in development costs. Contact us for a free consultation—we will assess your project at no cost.

Guarantees and Experience

The TrueTech team has 5+ years of experience in TypeScript and has developed over 50 fullstack projects using tRPC. We guarantee 100% type safety across all layers, full test coverage, transfer of code ownership and documentation, and post-delivery support.

Contact us to evaluate your project—we will analyze your architecture for free and propose the optimal solution. Order tRPC API development today and experience the efficiency of end-to-end typing.

API Development with REST, GraphQL, WebSocket, and tRPC

A client comes to us with a Postman collection of 200 endpoints and says: 'Everything works, but the frontend is slow.' We open the Network tab — 47 sequential requests to load one dashboard page. Each one waits for the previous. This is not a server speed issue — it's an API architecture problem. With 10 years on the market, we've redesigned dozens of such integrations, and we guarantee: the right protocol and contract solve the problem at its root.

When REST stops being enough

REST works well for simple CRUD operations. But as soon as a mobile app appears alongside the web interface, over-fetching begins: the mobile app requests /api/users/123 and gets a 4KB object, but only needs name and avatar. Multiply that by a list of 50 users — 200KB traffic instead of 8KB.

GraphQL solves this with selection sets. The client describes exactly the fields it needs, and the server returns only those. On a project with React Native + Next.js, we migrated from REST to Apollo Server: payload size on the main screen dropped from 340KB to 28KB — a 92% traffic savings. Our certified engineers confirm: the typical pain when adopting GraphQL is N+1 query. A resolver for the author field on a post calls SELECT * FROM users WHERE id = ? for each post in the list. On a page with 20 posts — 21 database queries. Solved with DataLoader — it batches queries and turns them into one SELECT * FROM users WHERE id IN (...).

What is tRPC and how is it better than REST/GraphQL?

If the entire stack is TypeScript (Next.js + Node/Bun), tRPC removes a whole layer of problems. You define a procedure on the server — the client gets full type-safety automatically, without code generation and without Swagger. Renamed a field in the Zod schema — TypeScript highlights all places on the frontend where it's used. tRPC reduces code by 2 times compared to REST + Swagger + openapi-typescript: no need to maintain a separate specification and generate types — everything is inferred from runtime validators. However, tRPC is not suitable if the API is consumed by third-party clients or mobile apps in other languages — in such cases we use GraphQL or REST with OpenAPI specification.

WebSocket and real-time: when SSE, when WS?

HTTP polling every 5 seconds is an illusion of real-time with up to 5 seconds delay and useless server load. For chats, live notifications, collaborative editing — WebSocket or Server-Sent Events. SSE is a one-way stream from server to client, works over ordinary HTTP, automatically reconnects. Suitable for notifications, data streaming, progress bars. WebSocket is bidirectional, needed for chats and collaborative features. Experience shows: 80% of 'real-time' tasks are solved with SSE, not WebSocket — fewer infrastructure complexities.

A typical mistake: opening a WebSocket connection for each page component. On one project, the dashboard opened 12 parallel WS connections. The correct approach is one connection manager at the application level, subscriptions through it. In our work results, we always transfer the connection scheme and a ready solution.

Protocol Typing Over-fetching Versioning Real-time
REST Weak (OpenAPI) Yes URL / Header Polling
GraphQL Strong (SDL) No Deprecation Subscriptions
tRPC Full (TypeScript) No TypeScript checks Subscriptions (optional)

Swagger / OpenAPI as a contract

Documentation written after the fact becomes outdated the day after release. We write the OpenAPI 3.1 specification before development starts; it becomes the contract between frontend and backend. The frontend generates types via openapi-typescript, the backend validates incoming data using generated schemas. Contract deviation from implementation is caught on CI, not during review. For Laravel — l5-swagger or dedoc/scramble. For Node.js — @fastify/swagger or Zod + zod-to-openapi.

How to properly authenticate an API?

JWT with long-lived access tokens without rotation is a source of problems when compromised. The correct scheme: access token for 15 minutes, refresh token for 30 days with rotation on each use. Refresh token stored in an httpOnly cookie, access token in memory (not in localStorage). For inter-service communication — API Keys with scope limitations or mTLS. OAuth 2.0 with PKCE for public clients (SPA, mobile).

How to handle versioning and backward compatibility?

Breaking changes in an API without versioning break clients. Three approaches we use in projects:

Method Example When to use
URL versioning /api/v2/ REST API with long-term legacy support
Header versioning Accept: application/vnd.api+json;version=2 Minimal URL changes
Evolutionary (deprecation) Adding fields, GraphQL deprecated directive For GraphQL — smooth field removal

We guarantee backward compatibility through automated checks (oasdiff) on CI.

How we develop APIs: step-by-step plan

  1. Analysis — audit of current integrations, data schema compilation, protocol selection (REST/GraphQL/tRPC/WebSocket).
  2. Contract design — OpenAPI or SDL (GraphQL) before the first line of code.
  3. Development — implementation per contract, unit tests for each endpoint.
  4. Load testing — k6: 500 virtual users, 10 minutes, p95 latency ≤ 200ms.
  5. Deployment — CI/CD with backward compatibility check, automatic documentation publication.
  6. Team training — handover of Postman collection or Playground, connection instructions.
Typical mistakes we eliminate
  • N+1 on queries without DataLoader.
  • No rate limiting — DDOS through unauthenticated endpoints.
  • Storing access token in localStorage.
  • Opening multiple WebSocket connections instead of a single connection manager.
  • Documentation not updated after release.

What is included (deliverables)

  • OpenAPI 3.1 specification (or SDL for GraphQL).
  • Generated client types for TypeScript / Dart / Kotlin.
  • Set of automated tests covering all endpoints (unit + integration).
  • Load tests (k6) and report (p50/p95/p99 latency, RPS).
  • Documentation in Swagger UI / Redoc / GraphiQL.
  • Team training (2–4 hour workshop).
  • Support for 30 days after delivery (per contract).

Our experience

  • 10+ years in the API development market.
  • 200+ completed projects (REST, GraphQL, WebSocket, tRPC).
  • 50+ certified engineers (AWS, Kubernetes, API Design).
  • Traffic savings averaging 85% when migrating from REST to GraphQL for mobile apps.
  • 100% backward compatibility — not a single broken client in the last 3 years.

Timeline

API development for a typical SaaS project with 30–50 endpoints: from 3 to 8 weeks depending on business logic complexity and number of external integrations. Migration of an existing REST API to GraphQL: from 2 to 6 weeks. Adding a WebSocket layer to an existing backend: from 1 to 3 weeks. Cost is calculated individually after an audit. Get a consultation — contact us to discuss your project.