Claude API Error Handling Best Practices

Handling errors correctly is what separates a demo integration from a production one. When you call the Claude API (or any LLM API), you will eventually hit rate limits, overloaded errors, malformed requests, timeouts, and transient network failures — and how your code reacts to those determines whether your users see a graceful retry or a broken app.

This guide covers the concrete error handling patterns you should implement: which status codes matter, how to structure retries with backoff, how to handle streaming failures mid-response, and how to keep your app resilient without masking real bugs.

Understand the error categories first

Before writing retry logic, classify errors into three buckets, because each needs a different response:

• Client errors (4xx) — bad request, invalid API key, malformed messages. Retrying won't help; you need to fix the request.
• Rate limit errors (429) — you're sending too many requests or tokens per minute. Retryable, but only after waiting.
• Server/transient errors (5xx, timeouts, connection resets) — temporary issues on the provider side. Retryable with backoff.

Treating all errors the same — either retrying everything or failing hard on everything — is the most common mistake. A 400 error retried in a loop just burns time and, if you're paying per request, money.

Build a status-code-aware handler

Your error handling should branch on the HTTP status code and, where available, the error type in the response body.

async function callClaudeAPI(payload) {
  const res = await fetch('https://api.subtoapi.app/v1/messages', {
    method: 'POST',
    headers: {
      'Authorization': `Bearer ${process.env.SUBTOAPI_KEY}`,
      'Content-Type': 'application/json',
    },
    body: JSON.stringify(payload),
  });

  if (res.ok) return res.json();

  const errorBody = await res.json().catch(() => ({}));

  switch (res.status) {
    case 400:
    case 422:
      throw new Error(`Invalid request: ${errorBody.error?.message || 'unknown'}`);
    case 401:
      throw new Error('Invalid or expired API key — check configuration, do not retry');
    case 429:
      throw new RateLimitError(res.headers.get('retry-after'));
    case 500:
    case 502:
    case 503:
    case 529:
      throw new TransientError(res.status);
    default:
      throw new Error(`Unexpected status ${res.status}: ${JSON.stringify(errorBody)}`);
  }
}

The key idea: don't swallow the distinction between "this will never work" and "this might work if I wait." Logging the raw error body also matters — you want enough detail to debug later, not just "request failed."

Retry with exponential backoff and jitter

For rate limit and transient errors, use exponential backoff with jitter rather than a fixed delay. Fixed delays cause every retrying client to hammer the API at the same moment, which makes rate limiting worse, not better.

async function withRetry(fn, maxAttempts = 5) {
  let attempt = 0;
  while (true) {
    try {
      return await fn();
    } catch (err) {
      attempt++;
      if (attempt >= maxAttempts) throw err;
      if (!(err instanceof RateLimitError) && !(err instanceof TransientError)) {
        throw err; // don't retry client errors
      }
      const base = err instanceof RateLimitError && err.retryAfter
        ? Number(err.retryAfter) * 1000
        : 2 ** attempt * 250;
      const jitter = Math.random() * 200;
      await new Promise(r => setTimeout(r, base + jitter));
    }
  }
}

A few details worth getting right:

• Respect Retry-After headers when present instead of guessing your own delay.
• Cap the number of attempts. Infinite retries hide real outages and can run up costs.
• Cap the maximum delay (e.g. 30–60 seconds) so a user-facing request doesn't hang indefinitely.

Handle timeouts explicitly

LLM responses can take several seconds, especially with long prompts or large outputs. Don't rely on default HTTP client timeouts — set one deliberately, and treat a timeout as a transient, retryable error, not a hard failure.

const controller = new AbortController();
const timeout = setTimeout(() => controller.abort(), 30000);

try {
  const res = await fetch(url, { ...options, signal: controller.signal });
} catch (err) {
  if (err.name === 'AbortError') {
    // treat as transient — retry or surface a "still working" state
  }
} finally {
  clearTimeout(timeout);
}

If you're building a chat UI, pair this with streaming (see /docs/streaming) so users see partial output as it arrives rather than waiting on a single long request that might time out.

Handle mid-stream failures separately

Streaming responses introduce a failure mode that non-streaming calls don't have: the connection can drop after you've already received partial content. Buffer what you've received, and decide per use case whether to discard it, show it with a "response interrupted" indicator, or resume with a follow-up request. Never silently retry from scratch after a partial stream without accounting for tokens already shown to the user — it's confusing and can duplicate content.

Log errors with enough context to debug later

At minimum, log:

• The status code and error type
• A request ID or timestamp for correlation
• Which model/endpoint was called
• Whether the call was retried, and how many times

This is especially important when running with a team (see /docs/messages for request/response structure) — you want to be able to tell whether an incident was a provider outage, a rate limit from shared usage, or a bug in your own request formatting.

Don't let error handling hide bugs

It's tempting to wrap everything in a broad try/catch and retry blindly. Resist this. A malformed request (bad JSON schema, invalid tool definition, missing required field) should fail loudly in development and logging, not get silently retried five times and then swallowed. Validate your request payloads before sending them — for tool use in particular, schema mistakes are a common source of 400 errors (see /docs/tools).

Where SubToAPI fits in

If you're exposing Claude access through your own application, SubToAPI gives you application-level API keys (sub_live_...), consistent HTTPS responses, and streaming support so you can build the retry and backoff logic described above against a stable, well-documented interface. Check /docs/quickstart to see the request/response shapes, or start a free trial at /signup.

Questions

What status code does the Claude API return for rate limiting? A 429 status code indicates you've exceeded your rate limit. Check for a Retry-After header and back off accordingly rather than retrying immediately.

Should I retry every failed API request? No. Retry only rate limit (429) and transient server errors (5xx, timeouts). Client errors like 400 or 401 indicate a problem with the request itself and won't succeed on retry.

How many retry attempts should I allow before failing? Three to five attempts with exponential backoff is typical for interactive applications. Cap total wait time so users aren't left waiting indefinitely, and surface a clear error if all attempts fail.