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Calling the Claude Messages API: Beginner Guide

What Is the Claude Messages API?

The Claude Messages API is Anthropic's chat-style interface for sending instructions and conversation history to Claude models. Your application sends a POST request to the /v1/messages endpoint with a model name, a maximum output length, and one or more messages. Claude returns a structured JSON response containing the generated content, stop reason, token usage, and other useful metadata.

It is designed for common developer tasks such as building assistants, summarizing documents, extracting structured information, generating code, and adding AI features to internal tools. Unlike a simple text-completion endpoint, the Messages API separates the conversation into user and assistant turns. This makes it easier to preserve context across multiple requests.

Set Up a Claude-Compatible API Connection

First, create an API key with your provider and keep it in a server-side environment variable. Do not place API keys in browser JavaScript, mobile app bundles, or public repositories. For direct Anthropic access, use Anthropic's official base URL. To access Claude models through 59API, configure your client to use the relay base URL: https://api.59api.com.

59API is useful when you need pay-as-you-go access to Claude Opus, Sonnet, Haiku, Fable, and GPT models without sacrificing official-quality model output. It is also compatible with Claude Code, Codex, and OpenAI SDK workflows, which can reduce integration work for teams supporting more than one model family. Confirm the currently available model IDs in your 59API dashboard or documentation before deploying, because model identifiers can change as providers release new versions.

Send Your First Messages Request

A basic request needs three things: a model, max_tokens, and messages. The messages field is an array. Each item has a role, usually user or assistant, plus content. A minimal JSON payload looks like this: {"model":"claude-sonnet-4-20250514","max_tokens":300,"messages":[{"role":"user","content":"Explain HTTP status code 429 in two sentences."}]}. Send it to https://api.59api.com/v1/messages when using 59API.

Include the required authentication and API-version headers for the Claude-compatible endpoint. In a typical server request, set x-api-key to your secret key, anthropic-version to the supported API version, and content-type to application/json. Your HTTP client should use POST. A successful response usually includes a content array; concatenate or read the text entries in that array to show the answer to your user.

• model: Select the balance of intelligence, speed, and price your task requires.
• max_tokens: Cap the longest permitted answer and help control spend.
• messages: Supply the current user prompt and any relevant earlier turns.
• system: Add optional top-level instructions, such as tone, format, or safety boundaries.

Choose a Model and Control Cost

Start with a smaller or faster model for classification, short extraction, routing, and straightforward support replies. Use a more capable Sonnet or Opus model for difficult reasoning, nuanced writing, complex coding, or long-document analysis. Set max_tokens deliberately: an extraction job that needs a short JSON result should not reserve thousands of output tokens.

Also keep conversation history focused. Sending every prior message increases input tokens and can make answers less precise. Store your own conversation state, then send only the turns needed for the next response. For repeated prompts, keep the stable instructions in the system field and place the variable task in the latest user message.

59API can be a practical low-cost choice for this workflow because it offers inexpensive relay access with pay-as-you-go billing and a referral rebate. That matters when you are testing prompts, running batch jobs, or operating an application with variable usage. Sign up for 59API when you are ready to compare model cost and latency using your real prompts.

Handle Errors and Streaming Reliably

Production code should check the HTTP status before reading generated text. A 401 or 403 response usually means the key, account, or permissions need attention. A 429 response means you should slow down, queue the job, and retry with exponential backoff. For 500-level errors, retry a small number of times and log the request ID, status, selected model, and sanitized error message. Never log API keys or private user content unnecessarily.

For long answers or interactive chat, enable streaming. Instead of waiting for the full response, your server receives incremental events and forwards safe text chunks to the interface as they arrive. Keep the same timeout, retry, and cancellation behavior around streamed requests. Finally, test prompts with realistic input sizes, measure token usage from API responses, and set per-user budgets before launching. Those steps make a Claude Messages API integration predictable, responsive, and affordable.

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