Serverless GraphQL APIs have become a go‑to solution for developers who need fast, scalable data layers without the overhead of managing servers. Cloudflare Workers, with their edge‑first architecture, make it especially easy to spin up a GraphQL endpoint that runs close to your users, cuts latency, and automatically scales to millions of requests. In this quick‑start guide we’ll walk through the essential steps: setting up a Worker, adding a GraphQL schema, wiring resolvers, and deploying everything with a single command.

First, create a free Cloudflare account and install the Wrangler CLI (`npm i -g @cloudflare/wrangler`). Wrangler is the official tool for building, testing, and publishing Workers. Run `wrangler init graphql‑worker –type=javascript` to scaffold a new project. The generated folder contains a `src/index.js` file where the Worker’s request handler lives, and a `wrangler.toml` file that defines the route and environment variables.

Next, add a GraphQL library. For a lightweight setup, `graphql-js` works perfectly: `npm install graphql`. Inside `src/index.js` import the necessary functions:

“`js
import { graphql, buildSchema } from “graphql”;
“`

Define a simple schema that mirrors the data you want to expose. For example, a tiny blog API could look like this:

“`js
const schema = buildSchema(`
type Post {
id: ID!
title: String!
content: String!
}

type Query {
posts: [Post]
post(id: ID!): Post
}
`);
“`

Now write resolvers that fetch data from wherever you store it—be it a Cloudflare KV namespace, a Supabase table, or an external REST service. Here’s a mock resolver using KV:

“`js
const resolvers = {
posts: async () => {
const list = await POST_KV.list();
return Promise.all(list.keys.map(async ({ name }) => {
const value = await POST_KV.get(name, { type: “json” });
return { id: name, …value };
}));
},
post: async ({ id }) => {
const value = await POST_KV.get(id, { type: “json” });
return value ? { id, …value } : null;
},
};
“`

The main fetch handler receives every HTTP request. Detect a POST to `/graphql`, extract the GraphQL query from the request body, and pass it to the `graphql` function:

“`js
export default {
async fetch(request, env) {
if (request.method === “POST” && new URL(request.url).pathname === “/graphql”) {
const { query, variables } = await request.json();
const result = await graphql({
schema,
source: query,
rootValue: resolvers,
variableValues: variables,
});
return new Response(JSON.stringify(result), {
headers: { “Content-Type”: “application/json” },
});
}
return new Response(“Not Found”, { status: 404 });
},
};
“`

With the code in place, bind a KV namespace in `wrangler.toml`:

“`toml
kv_namespaces = [
{ binding = “POST_KV”, id = “your-kv-id-here” }
]
“`

Run `wrangler dev` to test locally; the Worker will be reachable at `http://localhost:8787/graphql`. Use a tool like GraphiQL or Postman to issue queries and confirm you get the expected JSON payloads.

When you’re ready, publish with `wrangler publish`. Cloudflare will automatically route traffic to the nearest edge node, giving your GraphQL API sub‑millisecond response times for users worldwide. You can further lock down the endpoint with API tokens, enable caching for query results, or add schema stitching if you need to combine multiple data sources.

That’s all it takes: a few lines of schema, some resolvers, and a single `wrangler publish`. The result is a fully serverless GraphQL API that runs at the edge, costs virtually nothing beyond the KV storage you use, and scales without you lifting a finger. Happy building!