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1Scan for outdated or missing drivers - takes under a minute2Clear out junk files and repair common Windows errors3Fix the driver behind crashes, sound loss and screen glitchesTo scaffold a GraphQL server, create a schema that defines the API, resolver functions that supply field values, and an HTTP server that accepts GraphQL requests. For a small standalone Node.js service, Apollo Server provides a direct starter path; use NestJS when your application already follows Nest’s module structure, or GraphQL Yoga when you want its GraphQL-over-HTTP handler integrated with Node’s HTTP server.
This guide builds a locally queryable Apollo Server in JavaScript. Apollo’s getting-started documentation lists Node.js v20.0.0 or newer as a prerequisite. The examples are setup guidance, not a production security configuration; hosting choices and current package compatibility can affect the final setup.
What a GraphQL server scaffold needs
A working server has four basic parts:
- GraphQL runtime and server integration: GraphQL parses and executes operations; the server package handles HTTP requests and connects them to execution.
- Schema: The types and fields clients are allowed to query. Apollo’s getting-started documentation puts it simply: “Every GraphQL server (including Apollo Server) uses a schema to define the structure of data that clients can query.”
- Resolvers: Functions that provide the values for schema fields. A field can return data from a database, another service, or—in this minimal example—a local object.
- Listening process: An HTTP entry point that starts the server and exposes the GraphQL endpoint.
For a first scaffold, keep the data in memory so you can verify the schema and request path before introducing persistence or deployment-specific configuration.
Build a minimal Apollo Server
1. Create the project and install dependencies
Install Node.js v20.0.0 or newer, then make a project directory and initialize it:
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mkdir graphql-server
cd graphql-server
npm init -y
npm install @apollo/server graphqlUse an ES module entry point by adding "type": "module" to the generated package.json. For example:
{
"name": "graphql-server",
"version": "1.0.0",
"type": "module",
"scripts": {
"start": "node index.js"
}
}2. Define a schema and resolver
Create index.js. This example defines a Book type, a query for all books, and a query that looks up one book by ID:
import { ApolloServer } from '@apollo/server';
import { startStandaloneServer } from '@apollo/server/standalone';
const books = [
{ id: '1', title: 'The Hobbit', author: 'J. R. R. Tolkien' },
{ id: '2', title: 'Pride and Prejudice', author: 'Jane Austen' },
];
const typeDefs = `#graphql
type Book {
id: ID!
title: String!
author: String!
}
type Query {
books: [Book!]!
book(id: ID!): Book
}
`;
const resolvers = {
Query: {
books: () => books,
book: (_parent, { id }) => books.find((item) => item.id === id) ?? null,
},
};
const server = new ApolloServer({ typeDefs, resolvers });
const { url } = await startStandaloneServer(server, {
listen: { port: 4000 },
});
console.log(`Server ready at ${url}`);The schema marks id, title, and author as non-null with !. The list type [Book!]! means the list itself and every item in it must be non-null. The resolver for book returns null when no matching ID exists, which is allowed because that field is nullable.
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3. Start the server and send a query
Run the process:
npm startUse the URL printed in the terminal as the endpoint. With the standalone configuration above, it is normally http://localhost:4000/. Send a query with cURL:
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-H 'content-type: application/json'
--data '{"query":"{ books { id title author } }"}'A successful request returns JSON with a data object containing the selected fields. Try a specific book as well:
curl -X POST http://localhost:4000/
-H 'content-type: application/json'
--data '{"query":"query BookById($id: ID!) { book(id: $id) { title author } }","variables":{"id":"1"}}'GraphQL clients request only the fields named in the operation. The server still relies on the schema to validate the operation and on resolvers to produce the requested values.
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Choose a server path for the project
Apollo, NestJS, and Yoga are alternative fits rather than a universal ranking. Base the choice on the application you already have, how you want to author the schema, and the runtime or hosting integration you need.
| Option | Good fit | Schema approach and integration |
|---|---|---|
| Apollo Server | A standalone JavaScript or TypeScript GraphQL service, or a Node.js application that needs a documented framework or serverless integration. | Its getting-started path defines a schema and resolvers, then starts the server. Apollo documents integrations with several Node.js frameworks and serverless environments. |
| NestJS GraphQL | An application already using NestJS, or a team that wants GraphQL organized within Nest’s module conventions. | Supports code-first schemas generated from TypeScript decorators and classes, as well as schema-first GraphQL SDL. Nest documents both Apollo Server and Mercurius drivers; install and configure the driver appropriate to the project’s Nest version. |
| GraphQL Yoga v5 | A GraphQL-over-HTTP service where you want to provide a schema and connect Yoga’s handler to Node’s HTTP server. | The documented quick start installs graphql-yoga and graphql, creates a Yoga instance, and passes it to Node’s createServer. Its quick-start endpoint is /graphql; Yoga also supports different schema-building approaches. |
Apollo’s standalone example above is a reasonable starting point for a small Node service. If NestJS is already the application framework, use its GraphQL module and choose code-first or schema-first deliberately. For Yoga, follow its current v5 quick start rather than assuming Apollo’s server-start code applies to Yoga.
Make the scaffold fit the API
Choose schema-first or code-first based on how the team works
In the example, the schema is written as SDL in typeDefs, and resolver functions are defined separately in JavaScript. That is a schema-first style. NestJS also documents a code-first workflow in which TypeScript decorators and classes generate the schema. The right choice is a project convention: keep the schema and implementation understandable, and avoid adopting a second schema workflow without a concrete need.
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Replace in-memory data when the API needs persistence
The books array resets whenever the process restarts and is not shared between server instances. Replace resolver lookups with the application’s data-access layer when data must persist or be shared. The Guild’s Yoga tutorial is a learning path that extends a Node.js/TypeScript/Yoga server with Prisma and SQLite, validation, pagination, and filtering; those are not required dependencies for every scaffold.
Keep the HTTP integration appropriate to the runtime
The Apollo example uses its standalone server helper. Apollo also documents integrations for several Node.js frameworks and serverless environments; use the integration that matches the host rather than putting a standalone listener inside a framework or serverless handler. Yoga’s minimal Node example instead connects a Yoga instance to Node’s createServer.
Prepare the API for production
A server that answers a local query is not automatically ready for public traffic. Before exposing it, decide who can reach the API, which operations clients may run, how expensive queries can become, and how failures will be observed. Yoga’s production guidance discusses these as workload-dependent operational choices.
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- Control exposure: Decide whether the API is private to known clients or public. For a private API with controlled clients, persisted operations can restrict execution to operations registered by the developer.
- Limit costly operations: Public APIs may need query-cost controls. Yoga discusses limits such as maximum depth and controls involving directives and aliases. Choose protections based on the operations your schema permits and their real execution cost.
- Use caching where it helps: Response caching can reduce load on services or databases when the workload and data freshness requirements make cached results appropriate.
- Report failures: External error reporting, such as Sentry, is one option for diagnosing errors in a deployed service.
Do not treat disabling an in-browser IDE as a substitute for access control or query-cost protections. These are separate deployment decisions; select and verify controls for the clients and workload the API will actually serve.
Troubleshoot common scaffold problems
| Symptom | Likely cause | What to check |
|---|---|---|
| Installation or startup fails on the Apollo example. | The Node.js runtime is older than the documented prerequisite, or the project is not using the expected module configuration. | Check node --version against Apollo’s documented Node.js v20.0.0+ prerequisite. Confirm "type": "module" is present when using the import syntax shown here. |
| The endpoint cannot be reached. | The process did not start, is listening on another port, or the request is being sent to a different path than the configured server. | Look for the startup URL in the terminal, keep the server process running, and send the request to that host and port. The standalone example listens on port 4000. |
| The response reports a GraphQL validation error. | The operation asks for a field or argument that does not match the schema, or omits a required argument. | Compare the operation with typeDefs. In the example, book requires an id: ID! argument, and fields must be selected from the declared types. |
| A field is null or returns an unexpected value. | The resolver returned null, the lookup did not find a record, or the resolver’s data shape does not match the schema. |
Check the resolver and its data source. The example intentionally permits book to be null when the ID is unknown, while its books list and listed fields are non-null. |
| The API behaves differently after deploying. | The deployed runtime or framework integration differs from local standalone development, or production controls and dependencies differ. | Use the server integration intended for the deployment target, recheck current package and runtime requirements, and review exposure, query-cost, caching, and error-reporting choices for that environment. |
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