Your first API call

Get set up

First, grab an API key from platform.claude.com. You'll need to purchase some credits beforehand.

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Take the API key and store it in a .env.local file so it stays out of your version control. Hardcoding keys in source files is how they end up leaked on GitHub — keep them in environment files instead.

Next, install the SDK:

The anatomy of a request

Every API call goes through the messages.create function. You specify three things:

• A model — which Claude model handles the request
• A max tokens limit — a cap on how long the response can be
• A list of messages — objects with either user or assistant roles, structured similarly to how you'd have a conversation with Claude elsewhere

Here's what that looks like in its most basic form:

import Anthropic from "@anthropic-ai/sdk";

const client = new Anthropic();

const msg = await client.messages.create({
  model: "claude-sonnet-5",
  max_tokens: 2048,
  messages: [{
    role: "user",
    content: "Hello, Claude",
  }],
});

A real example: reviewing buggy code

Let's give Claude something a little more interesting than "hello." We'll point it at some buggy code and ask for a review. Here's the whole thing — one file, about 20 lines of code:

import Anthropic from "@anthropic-ai/sdk";

const client = new Anthropic();

const buggyCode = `
function add(a, b) {
  return a - b;
}
`;

const response = await client.messages.create({
  model: "claude-sonnet-5",
  max_tokens: 2048,
  system: "You are a terse senior code reviewer. Give feedback in one paragraph.",
  messages: [
    { role: "user", content: `Review this code:\n${buggyCode}` },
  ],
});

for (const block of response.content) {
  if (block.type === "text") {
    console.log(block.text);
  }
}

Two things to notice here:

1. The system prompt is where you shape the persona. I want a terse senior reviewer, not a chatty one — so I just say that.
2. The message.content in the response is an array of blocks, not a string. For a basic text reply there's usually just one block of type text, but Claude can return multiple blocks — text, tool calls, thinking — so we always loop and check the type.

Run it, and Claude spots that add is subtracting and tells you in one paragraph. That's it. That's the whole API call.

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From script to product

In a real product, this same messages.create shape is the engine behind something like a summarize endpoint. Pull a meeting transcript out of the database, hand it to Claude with a system prompt that says "extract insights and risks," save the result back on the row, and return it to the UI. It's the same call — just wrapped in a route handler.

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Recap

• Your first API call is a messages.create function with a model, a token limit, and messages.
• Store your API key in a .env.local file to keep it out of version control.
• Add a system prompt to shape Claude's behavior.
• The response content is an array of blocks — loop and check each block's type.
• From here, everything builds on this pattern.