Rate Limits

​

Rate Limit Tiers

​

Handling 429 Responses

{
  "detail": {
    "detail": "Rate limit exceeded",
    "code": "RATE_LIMITED"
  }
}

​

Recommended Strategy

1. Respect Retry-After — wait the specified number of seconds before retrying
2. Exponential backoff — if Retry-After is not present, use exponential backoff starting at 1 second
3. Cache responses — cache search results and skill details to reduce request volume
4. Batch operations — for bulk installs or updates, add a small delay (200-500ms) between requests

​

Example: Python with Retry

import time
import httpx

def api_request(url, headers, max_retries=3):
    for attempt in range(max_retries):
        response = httpx.get(url, headers=headers)

        if response.status_code == 429:
            retry_after = int(response.headers.get("Retry-After", 2 ** attempt))
            time.sleep(retry_after)
            continue

        return response

    raise Exception("Rate limit exceeded after retries")

​

Notes

• Rate limits are per IP address, not per user
• The CLI (ap command) includes built-in retry logic for rate-limited requests
• The MCP server plugin handles rate limits transparently
• If you need higher limits for integration purposes, contact us

​

Need Help?