maintainx-rate-limits

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Implement MaintainX API rate limiting, pagination, and backoff patterns. Use when handling rate limit errors, implementing retry logic, or optimizing API request throughput for MaintainX. Trigger with phrases like "maintainx rate limit", "maintainx throttling", "maintainx 429", "maintainx retry", "maintainx backoff", "maintainx pagination".

Install

mkdir -p .claude/skills/maintainx-rate-limits && curl -L -o skill.zip "https://mcp.directory/api/skills/download/6307" && unzip -o skill.zip -d .claude/skills/maintainx-rate-limits && rm skill.zip

Installs to .claude/skills/maintainx-rate-limits

About this skill

MaintainX Rate Limits

Overview

Handle MaintainX API rate limits gracefully with exponential backoff, cursor-based pagination, and request queuing to maximize throughput without triggering 429 errors.

Prerequisites

  • MaintainX API access configured
  • Node.js 18+ with axios
  • Understanding of async/await patterns

Instructions

Step 1: Rate-Limited Client Wrapper

// src/rate-limited-client.ts
import axios, { AxiosInstance, AxiosError } from 'axios';

export class RateLimitedClient {
  private http: AxiosInstance;
  private requestQueue: Array<() => void> = [];
  private activeRequests = 0;
  private maxConcurrent = 5;
  private minDelayMs = 100;  // 10 requests/second max

  constructor(apiKey?: string) {
    const key = apiKey || process.env.MAINTAINX_API_KEY;
    if (!key) throw new Error('MAINTAINX_API_KEY required');

    this.http = axios.create({
      baseURL: 'https://api.getmaintainx.com/v1',
      headers: {
        Authorization: `Bearer ${key}`,
        'Content-Type': 'application/json',
      },
      timeout: 30_000,
    });
  }

  private async throttle(): Promise<void> {
    if (this.activeRequests >= this.maxConcurrent) {
      await new Promise<void>((resolve) => this.requestQueue.push(resolve));
    }
    this.activeRequests++;
    await new Promise((r) => setTimeout(r, this.minDelayMs));
  }

  private release() {
    this.activeRequests--;
    const next = this.requestQueue.shift();
    if (next) next();
  }

  async request<T>(method: string, url: string, data?: any, params?: any): Promise<T> {
    await this.throttle();
    try {
      const response = await this.retryWithBackoff(
        () => this.http.request<T>({ method, url, data, params }),
      );
      return response.data;
    } finally {
      this.release();
    }
  }

  private async retryWithBackoff<T>(
    fn: () => Promise<T>,
    maxRetries = 3,
    baseDelay = 1000, // 1 second initial backoff delay
  ): Promise<T> {
    for (let attempt = 0; attempt <= maxRetries; attempt++) {
      try {
        return await fn();
      } catch (err) {
        const axiosErr = err as AxiosError;
        const status = axiosErr.response?.status;

        if (status !== 429 && !(status && status >= 500) || attempt === maxRetries) {
          throw err;
        }

        // Honor Retry-After header
        const retryAfter = axiosErr.response?.headers?.['retry-after'];
        const delayMs = retryAfter
          ? parseInt(retryAfter) * 1000
          : baseDelay * Math.pow(2, attempt) + Math.random() * 500;

        console.warn(
          `Rate limited (HTTP ${status}). Retry ${attempt + 1}/${maxRetries} in ${Math.round(delayMs)}ms`,
        );
        await new Promise((r) => setTimeout(r, delayMs));
      }
    }
    throw new Error('Unreachable');
  }
}

Step 2: Cursor-Based Pagination

MaintainX returns a cursor field in list responses. Pass it as a query parameter to fetch the next page.

async function paginateAll<T>(
  client: RateLimitedClient,
  endpoint: string,
  resultKey: string,
  params?: Record<string, any>,
): Promise<T[]> {
  const allItems: T[] = [];
  let cursor: string | undefined;

  do {
    const response: any = await client.request('GET', endpoint, undefined, {
      ...params,
      limit: 100,
      cursor,
    });
    const items = response[resultKey] as T[];
    allItems.push(...items);
    cursor = response.cursor ?? undefined;

    // Log progress for long-running operations
    if (allItems.length % 500 === 0) {
      console.log(`  Fetched ${allItems.length} items so far...`);
    }
  } while (cursor);

  return allItems;
}

// Usage
const allWorkOrders = await paginateAll(client, '/workorders', 'workOrders', {
  status: 'OPEN',
});
console.log(`Total: ${allWorkOrders.length} open work orders`);

Step 3: Batch Operations with p-queue

import PQueue from 'p-queue';

// 5 concurrent requests, max 10 per second
const queue = new PQueue({
  concurrency: 5,
  interval: 1000, // 1 second window for rate cap
  intervalCap: 10,
});

async function batchUpdate(
  client: RateLimitedClient,
  updates: Array<{ id: number; data: any }>,
) {
  const results = await Promise.allSettled(
    updates.map((update) =>
      queue.add(() =>
        client.request('PATCH', `/workorders/${update.id}`, update.data),
      ),
    ),
  );

  const succeeded = results.filter((r) => r.status === 'fulfilled').length;
  const failed = results.filter((r) => r.status === 'rejected').length;
  console.log(`Batch update: ${succeeded} succeeded, ${failed} failed`);
  return results;
}

// Close 100 completed work orders
const completedOrders = await paginateAll(
  client, '/workorders', 'workOrders', { status: 'COMPLETED' },
);

await batchUpdate(
  client,
  completedOrders.map((wo: any) => ({ id: wo.id, data: { status: 'CLOSED' } })),
);

Step 4: Rate Limit Monitoring

// src/rate-monitor.ts
class RateMonitor {
  private requests: number[] = [];
  private windowMs = 60_000; // 1 minute window

  record() {
    this.requests.push(Date.now());
    this.cleanup();
  }

  cleanup() {
    const cutoff = Date.now() - this.windowMs;
    this.requests = this.requests.filter((t) => t > cutoff);
  }

  getRate(): number {
    this.cleanup();
    return this.requests.length;
  }

  report() {
    const rate = this.getRate();
    const status = rate > 50 ? 'WARNING' : 'OK';
    console.log(`[RateMonitor] ${rate} req/min - ${status}`);
    return { rate, status };
  }
}

Output

  • Rate-limited client wrapper with built-in throttling and retry
  • Cursor-based pagination utility collecting all results
  • Batch operations with controlled concurrency via p-queue
  • Rate monitoring to track and alert on API usage

Error Handling

ScenarioStrategy
429 Too Many RequestsExponential backoff with jitter, honor Retry-After header
Retry-After header presentWait the specified number of seconds before retrying
Burst of requestsQueue with p-queue (concurrency: 5, intervalCap: 10/sec)
Large data sets (1000+ items)Paginate with limit: 100, delay between pages

Resources

Next Steps

For security configuration, see maintainx-security-basics.

Examples

Adaptive rate limiting based on response headers:

// Adjust concurrency dynamically based on remaining quota
function adaptRate(headers: Record<string, string>, queue: PQueue) {
  const remaining = parseInt(headers['x-ratelimit-remaining'] || '100');
  if (remaining < 10) {
    queue.concurrency = 1;
    console.warn('Approaching rate limit, reducing concurrency to 1');
  } else if (remaining < 50) {
    queue.concurrency = 3;
  } else {
    queue.concurrency = 5;
  }
}

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