Apify deploy integration
425 plugins, 2,810 skills, 200 agents for Claude Code. Open-source marketplace at tonsofskills.com with the ccpi CLI package manager.
npx -y skills add jeremylongshore/claude-code-plugins-plus-skills --skill apify-deploy-integrationAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
What its author says it does
Copied from the file, not written here
'Deploy Apify Actors and integrate scraping into external applications.
The file declares its own license as MIT. That is the author’s claim about this one file, and it is not the same thing as the license GitHub reports for the repository, which is listed with the other numbers below.
SKILL.md
5.5 KB, ~1.1k tokens by cl100k_base, as published. Nobody here has run it
Apify Deploy Integration
Overview
Deploy Actors to the Apify platform and integrate their results into external
applications. Covers apify push deployment, API-triggered runs from web apps
(synchronous and async patterns), webhook receivers, scheduled scraping pipelines,
and container deployment.
SKILL.md gives you the workflow and the core skeleton. Complete, copy-paste code for every pattern lives in references/implementation.md; end-to-end worked scenarios are in references/examples.md.
Prerequisites
- Actor tested locally (
apify run) apify logincompleted (stores CLI credentials)- Target application ready for integration
Authentication
Apps authenticate with an Apify API token. Generate one in Apify Console →
Settings → Integrations and expose it as the APIFY_TOKEN environment variable —
never hard-code it. The apify CLI uses its own credentials from apify login,
separate from APIFY_TOKEN. Full auth notes: references/implementation.md.
Instructions
Step 1: Deploy the Actor to the platform
# Push Actor code to Apify
apify push
# Push to a specific Actor (creates if it doesn't exist)
apify push username/my-scraper
# Pull an existing Actor to modify
apify pull username/existing-actor
Step 2: Trigger the Actor from your app
Instantiate ApifyClient with your token, then either call() (blocks until the
run finishes) or start() (returns immediately for polling). Here is the core
synchronous skeleton:
import { ApifyClient } from 'apify-client';
const client = new ApifyClient({ token: process.env.APIFY_TOKEN });
const run = await client.actor('username/product-scraper').call({
startUrls: [{ url: 'https://store.example.com' }],
maxItems: 500,
});
if (run.status !== 'SUCCEEDED') throw new Error(run.statusMessage);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
The full typed service — scrapeProducts (blocking), startScrape +
getScrapeResults (async poll) — is in
references/implementation.md.
Step 3: Choose an integration pattern
Pick the pattern that matches your app, then copy the full handler from the reference:
- Next.js API route — start a run in a
POST, poll by run ID in aGET. Avoids serverless timeouts. See implementation.md. - Express webhook receiver — register an Apify webhook and react on
ACTOR.RUN.SUCCEEDED/FAILED/TIMED_OUT. See implementation.md. - Scheduled pipeline — run on cron/Apify Schedule, export CSV, archive to a named dataset. See implementation.md.
- Docker / Cloud Run — containerize an app that calls Apify, inject the token as a secret. See implementation.md.
Rule of thumb: poll for request/response UX (a user waits on a result); use webhooks for fire-and-forget pipelines (scheduled scrapes, background enrichment).
Output
- A deployed Actor on the Apify platform (
apify pushbuild succeeds) - An integration module (
src/services/apify.ts) exposing blocking + async calls - API routes / webhook receivers wired into your app's framework
- Structured results read from the Actor's default dataset (JSON or CSV export)
- Optional date-stamped archive in a named dataset for historical access
Error Handling
| Issue | Cause | Solution |
|---|---|---|
apify push fails | Auth or build error | Check apify login and Dockerfile |
| Webhook not received | URL unreachable from internet | Use ngrok for dev; verify HTTPS in prod |
| Timeout in API route | Actor takes too long | Use async pattern (start + poll) |
| Memory error on platform | Actor needs more RAM | Increase memory option |
| Large dataset download | >100MB results | Use pagination or streaming |
Examples
Three end-to-end scenarios — synchronous script call, non-blocking Next.js API, and a scheduled CSV-export pipeline — are worked through in references/examples.md. Minimal blocking call:
import { scrapeProducts } from './services/apify';
const products = await scrapeProducts(['https://store.example.com/p/1']);
console.log(`Got ${products.length} products`);
Resources
Next Steps
For webhook event handling in depth, see the apify-webhooks-events skill. For the
full integration code referenced above, see
references/implementation.md.