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Apollo Server

Organization
apollographql
apollo-server

Guide for building GraphQL servers with Apollo Server 5.x. Use this skill when: (1) setting up a new Apollo Server project, (2) writing resolvers or defining GraphQL schemas, (3) implementing authentication or authorization, (4) creating plugins or custom data sources, (5) troubleshooting Apollo Server errors or performance issues.

Overview

Publisherapollographql
Repositoryskills
Skill nameapollo-server
Stars
112
Forks
12
Bundled files
6
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 6 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by apollographql on GitHub. Read the source before you install it.

Installation

Install the Apollo Server AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/apollographql/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/skills/apollo-server .claude/skills/apollo-server
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Apollo Server in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Apollo Server on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Apollo Server is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Apollo Server 5.x Guide

Apollo Server is an open-source GraphQL server that works with any GraphQL schema. Apollo Server 5 is framework-agnostic and runs standalone or integrates with Express, Fastify, and serverless environments.

Quick Start

Step 1: Install

bash
npm install @apollo/server graphql

For Express integration:

bash
npm install @apollo/server @as-integrations/express5 express graphql cors

Step 2: Define Schema

typescript
const typeDefs = `#graphql
  type Book {
    title: String
    author: String
  }

  type Query {
    books: [Book]
  }
`;

Step 3: Write Resolvers

typescript
const resolvers = {
  Query: {
    books: () => [
      { title: "The Great Gatsby", author: "F. Scott Fitzgerald" },
      { title: "1984", author: "George Orwell" },
    ],
  },
};

Step 4: Start Server

Standalone (Recommended for prototyping):

The standalone server is great for prototyping, but for production services, we recommend integrating Apollo Server with a more fully-featured web framework such as Express, Koa, or Fastify. Swapping from the standalone server to a web framework later is straightforward.

typescript
import { ApolloServer } from "@apollo/server";
import { startStandaloneServer } from "@apollo/server/standalone";

const server = new ApolloServer({ typeDefs, resolvers });

const { url } = await startStandaloneServer(server, {
  listen: { port: 4000 },
});

console.log(`Server ready at ${url}`);

Express:

typescript
import { ApolloServer } from "@apollo/server";
import { expressMiddleware } from "@as-integrations/express5";
import { ApolloServerPluginDrainHttpServer } from "@apollo/server/plugin/drainHttpServer";
import express from "express";
import http from "http";
import cors from "cors";

const app = express();
const httpServer = http.createServer(app);

const server = new ApolloServer({
  typeDefs,
  resolvers,
  plugins: [ApolloServerPluginDrainHttpServer({ httpServer })],
});

await server.start();

app.use(
  "/graphql",
  cors(),
  express.json(),
  expressMiddleware(server, {
    context: async ({ req }) => ({ token: req.headers.authorization }),
  }),
);

await new Promise<void>((resolve) => httpServer.listen({ port: 4000 }, resolve));
console.log("Server ready at http://localhost:4000/graphql");

Schema Definition

Scalar Types

  • Int - 32-bit integer
  • Float - Double-precision floating-point
  • String - UTF-8 string
  • Boolean - true/false
  • ID - Unique identifier (serialized as String)

Type Definitions

graphql
type User {
  id: ID!
  name: String!
  email: String
  posts: [Post!]!
}

type Post {
  id: ID!
  title: String!
  content: String
  author: User!
}

input CreatePostInput {
  title: String!
  content: String
}

type Query {
  user(id: ID!): User
  users: [User!]!
}

type Mutation {
  createPost(input: CreatePostInput!): Post!
}

Enums and Interfaces

graphql
enum Status {
  DRAFT
  PUBLISHED
  ARCHIVED
}

interface Node {
  id: ID!
}

type Article implements Node {
  id: ID!
  title: String!
}

Resolvers Overview

Resolvers follow the signature: (parent, args, contextValue, info)

  • parent: Result from parent resolver (root resolvers receive undefined)
  • args: Arguments passed to the field
  • contextValue: Shared context object (auth, dataSources, etc.)
  • info: Field-specific info and schema details (rarely used)
typescript
const resolvers = {
  Query: {
    user: async (_, { id }, { dataSources }) => {
      return dataSources.usersAPI.getUser(id);
    },
  },
  User: {
    posts: async (parent, _, { dataSources }) => {
      return dataSources.postsAPI.getPostsByAuthor(parent.id);
    },
  },
  Mutation: {
    createPost: async (_, { input }, { dataSources, user }) => {
      if (!user) throw new GraphQLError("Not authenticated");
      return dataSources.postsAPI.create({ ...input, authorId: user.id });
    },
  },
};

Context Setup

Context is created per-request and passed to all resolvers.

typescript
interface MyContext {
  token?: string;
  user?: User;
  dataSources: {
    usersAPI: UsersDataSource;
    postsAPI: PostsDataSource;
  };
}

const server = new ApolloServer<MyContext>({
  typeDefs,
  resolvers,
});

// Standalone
const { url } = await startStandaloneServer(server, {
  context: async ({ req }) => ({
    token: req.headers.authorization || "",
    user: await getUser(req.headers.authorization || ""),
    dataSources: {
      usersAPI: new UsersDataSource(),
      postsAPI: new PostsDataSource(),
    },
  }),
});

// Express middleware
expressMiddleware(server, {
  context: async ({ req, res }) => ({
    token: req.headers.authorization,
    user: await getUser(req.headers.authorization),
    dataSources: {
      usersAPI: new UsersDataSource(),
      postsAPI: new PostsDataSource(),
    },
  }),
});

Reference Files

Detailed documentation for specific topics:

Key Rules

Schema Design

  • Use ! (non-null) for fields that always have values
  • Prefer input types for mutations over inline arguments
  • Use interfaces for polymorphic types
  • Keep schema descriptions for documentation

Resolver Best Practices

  • Keep resolvers thin - delegate to services/data sources
  • Always handle errors explicitly
  • Use DataLoader for batching related queries
  • Return partial data when possible (GraphQL's strength)

Performance

  • Use @defer and @stream for large responses
  • Implement DataLoader to solve N+1 queries
  • Consider persisted queries for production
  • Use caching headers and CDN where appropriate

Ground Rules

  • ALWAYS use Apollo Server 5.x patterns (not v4 or earlier)
  • ALWAYS type your context with TypeScript generics
  • ALWAYS use GraphQLError from graphql package for errors
  • NEVER expose stack traces in production errors
  • PREFER startStandaloneServer for prototyping only
  • USE an integration with a server framework like Express, Koa, Fastify, Next, etc. for production apps
  • IMPLEMENT authentication in context, authorization in resolvers

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Apollo Server AI skill do?

Guide for building GraphQL servers with Apollo Server 5.x. Use this skill when: (1) setting up a new Apollo Server project, (2) writing resolvers or defining GraphQL schemas, (3) implementing authentication or authorization, (4) creating plugins or custom data sources, (5) troubleshooting Apollo Server errors or performance issues.

Why use Apollo Server on TypingMind?

Because you install it once and use it with any model. Apollo Server is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Apollo Server in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/apollographql/skills/tree/main/skills/apollo-server. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Apollo Server?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Apollo Server?

As many as you like. As long as a model supports skills, you can use Apollo Server with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Apollo Server AI skill free?

Yes. It is published on GitHub by apollographql under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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