Rate Limits - Modrinth

The Modrinth API implements rate limiting to ensure fair usage and maintain service quality for all users. Rate limits are applied per IP address using the GCRA (Generic Cell Rate Algorithm).

Rate Limit Configuration

Default Limits

The API enforces the following rate limits:

300 requests per minute per IP address
Burst capacity: 300 requests

Rate limits are the same whether you use an authenticated request (with a token) or an unauthenticated request.

How GCRA Works

Modrinth uses GCRA for smooth rate limiting:

Requests are allowed at a steady rate (300/minute = 5 requests/second)
You can burst up to 300 requests at once
After a burst, you must wait for the rate limit to replenish
The algorithm prevents thundering herd effects

Rate Limit Headers

Every API response includes rate limit information in the headers:

X-Ratelimit-Limit: 300
X-Ratelimit-Remaining: 245
X-Ratelimit-Reset: 42

Header Descriptions

X-Ratelimit-Limit

integer

The maximum number of requests allowed per minute (always 300)

X-Ratelimit-Remaining

integer

The number of requests remaining in the current rate limit window

X-Ratelimit-Reset

integer

The time in seconds until the rate limit fully resets

Monitoring Rate Limits

Always check these headers to avoid hitting rate limits:

const response = await fetch('https://api.modrinth.com/v2/search', {
  headers: { 'User-Agent': 'my-app/1.0.0' }
});

const limit = response.headers.get('X-Ratelimit-Limit');
const remaining = response.headers.get('X-Ratelimit-Remaining');
const reset = response.headers.get('X-Ratelimit-Reset');

console.log(`Rate limit: ${remaining}/${limit}, resets in ${reset}s`);

if (remaining < 10) {
  console.warn('Approaching rate limit!');
}

Rate Limit Exceeded

When you exceed the rate limit, the API returns a 429 Too Many Requests response.

429 Response Example

HTTP/1.1 429 Too Many Requests
Content-Type: application/json
X-Ratelimit-Limit: 300
X-Ratelimit-Remaining: 0
X-Ratelimit-Reset: 15
Retry-After: 15

{
  "error": "ratelimit_error",
  "description": "You are being rate-limited. Please wait 15000 milliseconds. 0/300 remaining."
}

Response Headers on 429

Retry-After

integer

The number of seconds to wait before making another request

X-Ratelimit-Remaining

integer

Will be 0 when rate limited

X-Ratelimit-Reset

integer

Seconds until you can make requests again

Handling Rate Limits

Basic Retry Logic

Implement exponential backoff when you receive a 429:

async function fetchWithRetry(url, options = {}, maxRetries = 3) {
  for (let i = 0; i < maxRetries; i++) {
    const response = await fetch(url, {
      ...options,
      headers: {
        'User-Agent': 'my-app/1.0.0',
        ...options.headers
      }
    });
    
    if (response.status !== 429) {
      return response;
    }
    
    // Rate limited - wait before retrying
    const retryAfter = response.headers.get('Retry-After');
    const waitTime = retryAfter ? parseInt(retryAfter) * 1000 : Math.pow(2, i) * 1000;
    
    console.log(`Rate limited. Waiting ${waitTime}ms before retry...`);
    await new Promise(resolve => setTimeout(resolve, waitTime));
  }
  
  throw new Error('Max retries exceeded');
}

// Usage
try {
  const response = await fetchWithRetry('https://api.modrinth.com/v2/search');
  const data = await response.json();
} catch (error) {
  console.error('Request failed:', error);
}

Advanced Rate Limit Management

Use a token bucket or queue to manage requests:

class RateLimiter {
  constructor(maxRequests = 300, perMilliseconds = 60000) {
    this.maxRequests = maxRequests;
    this.perMilliseconds = perMilliseconds;
    this.requests = [];
  }
  
  async waitForToken() {
    const now = Date.now();
    // Remove requests older than the time window
    this.requests = this.requests.filter(
      time => now - time < this.perMilliseconds
    );
    
    if (this.requests.length >= this.maxRequests) {
      const oldestRequest = this.requests[0];
      const waitTime = this.perMilliseconds - (now - oldestRequest);
      
      console.log(`Rate limit reached. Waiting ${waitTime}ms...`);
      await new Promise(resolve => setTimeout(resolve, waitTime));
      
      return this.waitForToken();
    }
    
    this.requests.push(now);
  }
  
  async fetch(url, options = {}) {
    await this.waitForToken();
    return fetch(url, {
      ...options,
      headers: {
        'User-Agent': 'my-app/1.0.0',
        ...options.headers
      }
    });
  }
}

// Usage
const limiter = new RateLimiter();

for (let i = 0; i < 1000; i++) {
  const response = await limiter.fetch('https://api.modrinth.com/v2/search');
  console.log(`Request ${i + 1} completed`);
}

Python Example with Backoff

import requests
import time
from requests.adapters import HTTPAdapter
from requests.packages.urllib3.util.retry import Retry

def create_session():
    session = requests.Session()
    
    # Configure retry strategy for rate limits
    retry_strategy = Retry(
        total=5,
        status_forcelist=[429, 500, 502, 503, 504],
        allowed_methods=["GET", "POST", "PUT", "DELETE"],
        backoff_factor=2  # 2, 4, 8, 16, 32 seconds
    )
    
    adapter = HTTPAdapter(max_retries=retry_strategy)
    session.mount("https://", adapter)
    session.mount("http://", adapter)
    
    return session

def make_request(session, url):
    headers = {'User-Agent': 'my-app/1.0.0'}
    
    response = session.get(url, headers=headers)
    
    # Check remaining rate limit
    remaining = response.headers.get('X-Ratelimit-Remaining')
    if remaining and int(remaining) < 10:
        print(f"Warning: Only {remaining} requests remaining")
    
    return response

# Usage
session = create_session()
response = make_request(session, 'https://api.modrinth.com/v2/search')
print(response.json())

Best Practices

1. Respect Rate Limit Headers

Always check X-Ratelimit-Remaining before making bulk requests:

if (remaining < requiredRequests) {
  const waitTime = resetSeconds * 1000;
  await sleep(waitTime);
}

2. Implement Caching

Cache API responses to reduce the number of requests:

const cache = new Map();
const CACHE_TTL = 5 * 60 * 1000; // 5 minutes

async function fetchWithCache(url) {
  const cached = cache.get(url);
  
  if (cached && Date.now() - cached.timestamp < CACHE_TTL) {
    return cached.data;
  }
  
  const response = await fetch(url, {
    headers: { 'User-Agent': 'my-app/1.0.0' }
  });
  const data = await response.json();
  
  cache.set(url, { data, timestamp: Date.now() });
  return data;
}

3. Batch Requests

Use bulk endpoints when available:

# Instead of multiple single requests
curl "https://api.modrinth.com/v2/project/fabric-api"
curl "https://api.modrinth.com/v2/project/sodium"
curl "https://api.modrinth.com/v2/project/lithium"

# Use the bulk endpoint
curl "https://api.modrinth.com/v2/projects?ids=[\"fabric-api\",\"sodium\",\"lithium\"]"

4. Spread Out Requests

Don’t burst all requests at once. Spread them over time:

async function processItems(items, processFn, requestsPerSecond = 5) {
  const delay = 1000 / requestsPerSecond;
  
  for (const item of items) {
    await processFn(item);
    await new Promise(resolve => setTimeout(resolve, delay));
  }
}

// Process 300 items at 5 requests/second (60 seconds total)
await processItems(projects, async (project) => {
  const response = await fetch(`https://api.modrinth.com/v2/project/${project}`);
  return response.json();
});

5. Use Conditional Requests

Use If-None-Match headers with ETags to avoid downloading unchanged data:

const etags = new Map();

async function fetchConditional(url) {
  const headers = { 'User-Agent': 'my-app/1.0.0' };
  const etag = etags.get(url);
  
  if (etag) {
    headers['If-None-Match'] = etag;
  }
  
  const response = await fetch(url, { headers });
  
  if (response.status === 304) {
    console.log('Data unchanged, using cached version');
    return null; // Use cached data
  }
  
  // Store new ETag
  const newEtag = response.headers.get('ETag');
  if (newEtag) {
    etags.set(url, newEtag);
  }
  
  return response.json();
}

6. Monitor Your Usage

Track your API usage over time:

class UsageMonitor {
  constructor() {
    this.requests = [];
    this.rateLimitHits = 0;
  }
  
  recordRequest(response) {
    this.requests.push({
      timestamp: Date.now(),
      status: response.status,
      remaining: response.headers.get('X-Ratelimit-Remaining')
    });
    
    if (response.status === 429) {
      this.rateLimitHits++;
    }
  }
  
  getStats() {
    const now = Date.now();
    const lastMinute = this.requests.filter(
      r => now - r.timestamp < 60000
    );
    
    return {
      totalRequests: this.requests.length,
      requestsLastMinute: lastMinute.length,
      rateLimitHits: this.rateLimitHits
    };
  }
}

Rate Limit Exemptions

Internal Rate Limit Key

Modrinth provides a special rate limit bypass key for internal services. This is not available to public API users.

Do not attempt to use or guess the internal rate limit key. Unauthorized use may result in your IP being blocked.

Requesting Higher Limits

If you have a legitimate use case requiring higher rate limits:

Document your use case: Explain why you need higher limits
Show optimization efforts: Demonstrate you’ve implemented caching and batching
Provide contact information: Include your project details and contact info
Contact Modrinth: Email [email protected]

Higher rate limits are granted on a case-by-case basis for projects that benefit the Modrinth ecosystem.

Cloudflare Integration

Modrinth uses Cloudflare for DDoS protection. The API checks for the CF-Connecting-IP header when Cloudflare integration is enabled.

IP Detection

Rate limits are applied based on:

CF-Connecting-IP header (if Cloudflare is enabled)
Request peer address (fallback)

Using a proxy or VPN may cause you to share a rate limit with other users on the same IP address.

Troubleshooting

Issue: Rate Limited Despite Low Usage

Possible causes:

Sharing an IP with other users (VPN, corporate network, cloud provider)
Multiple applications using the same IP
Burst of requests exceeding the limit

Solutions:

Implement request spreading (5 requests/second max)
Use caching to reduce requests
Contact Modrinth if you have a dedicated IP and still face issues

Issue: Inconsistent Rate Limit Headers

Possible causes:

Redis connectivity issues (API falls back to reduced limits)
Multiple API servers with slightly different state

Solutions:

Don’t rely on exact values, use headers as guidance
Implement retry logic for all requests

Issue: 401 Instead of 429

Cause: If the API cannot determine your IP address, you’ll receive a 401 error:

{
  "error": "unauthorized",
  "description": "Unable to obtain user IP address!"
}

Solution:

Check your network configuration
Ensure you’re not blocking necessary headers
Contact support if the issue persists

Summary

Current Limit

300 requests per minute per IP address with burst capacity

Headers

Monitor X-Ratelimit-Remaining and X-Ratelimit-Reset headers

429 Response

Implement exponential backoff using the Retry-After header

Best Practices

Cache responses, batch requests, and spread traffic over time

Next Steps

Error Handling

Learn about all API error codes and responses

API Overview

Return to the API overview page

Getting Started

Core Resources

Content & Search

Server Hosting API

Client Libraries

​Rate Limit Configuration

​Default Limits

​How GCRA Works

​Rate Limit Headers

​Header Descriptions

​Monitoring Rate Limits

​Rate Limit Exceeded

​429 Response Example

​Response Headers on 429

​Handling Rate Limits

​Basic Retry Logic

​Advanced Rate Limit Management

​Python Example with Backoff

​Best Practices

​1. Respect Rate Limit Headers

​2. Implement Caching

​3. Batch Requests

​4. Spread Out Requests

​5. Use Conditional Requests

​6. Monitor Your Usage

​Rate Limit Exemptions

​Internal Rate Limit Key

​Requesting Higher Limits

​Cloudflare Integration

​IP Detection

​Troubleshooting

​Issue: Rate Limited Despite Low Usage

​Issue: Inconsistent Rate Limit Headers

​Issue: 401 Instead of 429

​Summary

Current Limit

Headers

429 Response

Best Practices

​Next Steps

Error Handling

API Overview

Rate Limit Configuration

Default Limits

How GCRA Works

Rate Limit Headers

Header Descriptions

Monitoring Rate Limits

Rate Limit Exceeded

429 Response Example

Response Headers on 429

Handling Rate Limits

Basic Retry Logic

Advanced Rate Limit Management

Python Example with Backoff

Best Practices

1. Respect Rate Limit Headers

2. Implement Caching

3. Batch Requests

4. Spread Out Requests

5. Use Conditional Requests

6. Monitor Your Usage

Rate Limit Exemptions

Internal Rate Limit Key

Requesting Higher Limits

Cloudflare Integration

IP Detection

Troubleshooting

Issue: Rate Limited Despite Low Usage

Issue: Inconsistent Rate Limit Headers

Issue: 401 Instead of 429

Summary

Next Steps