From apify-agent-skills
Integrates Apify web scraping and automation into existing JS/TS or Python apps using the apify-client package. Use to call Actors, retrieve results, and integrate into data pipelines.
How this skill is triggered — by the user, by Claude, or both
Slash command
/apify-agent-skills:apify-sdk-integrationThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
Add Apify Actor execution to an existing application. This skill covers the `apify-client` package for JS/TS and Python, plus the REST API for other languages.
Add Apify Actor execution to an existing application. This skill covers the apify-client package for JS/TS and Python, plus the REST API for other languages.
apify-clientis the API client for calling Actors from your app.apifyis the SDK for building Actors (wrong package for this use case).Always install
apify-client. Never installapifyfor integration work.
The user needs an APIFY_TOKEN. Direct them to Console > Settings > Integrations at https://console.apify.com/settings/integrations to create one. If they don't have an account: https://console.apify.com/sign-up (free, no credit card).
Store the token securely — environment variable or secrets manager, never hardcoded.
Before writing integration code, find the Actor that fits the user's needs. Use the MCP tools if available:
search-actors — search the Apify Store by keywordfetch-actor-details — get the Actor's input schema, output format, and pricingAlternatively, browse https://apify.com/store. Append .md to any Actor's Store URL to get its docs in markdown.
npm install apify-client
import { ApifyClient } from 'apify-client';
const client = new ApifyClient({ token: process.env.APIFY_TOKEN });
const run = await client.actor('apify/web-scraper').call({
startUrls: [{ url: 'https://example.com' }],
maxPagesPerCrawl: 10,
});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
.call() blocks until the Actor finishes. Use for short-running Actors (under a few minutes).
const run = await client.actor('apify/web-scraper').start({
startUrls: [{ url: 'https://example.com' }],
});
// Poll for completion
const finishedRun = await client.run(run.id).waitForFinish();
// Retrieve results
const { items } = await client.dataset(finishedRun.defaultDatasetId).listItems();
Use .start() + .waitForFinish() for long-running Actors or when you need the run ID immediately.
// Dataset items (structured data from pushData)
const { items } = await client.dataset(run.defaultDatasetId).listItems({
limit: 100,
offset: 0,
});
// Key-value store (files, screenshots, etc.)
const record = await client.keyValueStore(run.defaultKeyValueStoreId).getRecord('OUTPUT');
try {
const run = await client.actor('apify/web-scraper').call(input);
if (run.status !== 'SUCCEEDED') {
const log = await client.log(run.id).get();
throw new Error(`Actor failed with status ${run.status}: ${log}`);
}
const { items } = await client.dataset(run.defaultDatasetId).listItems();
} catch (error) {
if (error.message?.includes('not found')) {
// Actor ID is wrong or Actor was deleted
} else if (error.statusCode === 401) {
// Invalid or missing APIFY_TOKEN
}
throw error;
}
pip install apify-client
from apify_client import ApifyClient
import os
client = ApifyClient(token=os.environ['APIFY_TOKEN'])
run = client.actor('apify/web-scraper').call(run_input={
'startUrls': [{'url': 'https://example.com'}],
'maxPagesPerCrawl': 10,
})
items = client.dataset(run['defaultDatasetId']).list_items().items
run = client.actor('apify/web-scraper').start(run_input={
'startUrls': [{'url': 'https://example.com'}],
})
# Poll for completion
finished_run = client.run(run['id']).wait_for_finish()
items = client.dataset(finished_run['defaultDatasetId']).list_items().items
from apify_client import ApifyClientAsync
client = ApifyClientAsync(token=os.environ['APIFY_TOKEN'])
run = await client.actor('apify/web-scraper').call(run_input={
'startUrls': [{'url': 'https://example.com'}],
})
items = (await client.dataset(run['defaultDatasetId']).list_items()).items
For languages without an official client, use the REST API directly.
POST https://api.apify.com/v2/acts/{actorId}/runs
Authorization: Bearer <APIFY_TOKEN>
Content-Type: application/json
{ "startUrls": [{ "url": "https://example.com" }] }
GET https://api.apify.com/v2/acts/{actorId}/runs/{runId}
Authorization: Bearer <APIFY_TOKEN>
GET https://api.apify.com/v2/datasets/{datasetId}/items?format=json
Authorization: Bearer <APIFY_TOKEN>
Full API reference: https://docs.apify.com/api/v2
timeoutSecs in the Actor input or use waitSecs on .call() to avoid indefinite waits.limit and offset when retrieving dataset items. Default limit is 250K items.ApifyClient instance and reuse it across calls.fetch-actor-details MCP tool or append .md to the Actor's Store URL to get the schema before constructing input.If the Apify MCP server is available, use search-apify-docs and fetch-apify-docs tools for contextual documentation lookups during development.
npx claudepluginhub apify/agent-skills --plugin apify-actor-commandsRuns a sample Apify Actor via apify-client to crawl sites and fetch results. For initial Apify setup, connectivity tests, or learning actor invocation and dataset retrieval.
Develop, debug, and deploy Apify Actors — serverless cloud programs for web scraping, automation, and data processing. Guides setup, template selection, and CLI usage.
Creates, modifies, and debugs Apify Actor projects. Guides CLI setup, authentication, project bootstrap, and deployment.