Universal web scraper

AI-driven data extraction from ~100 Actors across 15+ platforms via the Apify CLI.

Rule: Always pass --json and redirect stderr with 2>/dev/null to CLI commands. JSON output is stable across CLI versions. stderr contains progress messages that break JSON parsers if not redirected.

Prerequisites

• Apify CLI v1.4.0+ (npm install -g apify-cli)
• Authenticated session (see below)

Authentication

If a CLI command fails with an auth error, authenticate using one of these methods:

1. OAuth (interactive): apify login (opens browser)
2. Environment variable: export APIFY_TOKEN=your_token_here
3. From .env file: source .env (if the file contains APIFY_TOKEN=...)

Generate token: https://console.apify.com/settings/integrations

Workflow

Step 1: Understand goal and select Actor

Identify the target platform and use case. Read references/actor-index.md to find the right Actor.

If the task involves a multi-step pipeline, also read the matching workflow guide:

Task involves...	Read
leads, contacts, emails, B2B	references/workflows/lead-generation.md
competitor, ads, pricing	references/workflows/competitive-intel.md
influencer, creator	references/workflows/influencer-vetting.md
brand, mentions, sentiment	references/workflows/brand-monitoring.md
reviews, ratings, reputation	references/workflows/review-analysis.md
SEO, SERP, crawl, content, RAG	references/workflows/content-and-seo.md
analytics, engagement, performance	references/workflows/social-media-analytics.md
trends, keywords, hashtags	references/workflows/trend-research.md
jobs, recruiting, candidates	references/workflows/job-market-and-recruitment.md
real estate, listings, hotels	references/workflows/real-estate-and-hospitality.md
price monitoring, e-commerce, products	references/workflows/ecommerce-price-monitoring.md
contact enrichment, email extraction	references/workflows/contact-enrichment.md
knowledge base, RAG, LLM data feed	references/workflows/knowledge-base-and-rag.md
company research, due diligence	references/workflows/company-research.md

If no Actor matches in the index, search dynamically:

apify actors search "KEYWORDS" --json --limit 10 2>/dev/null

From results: items[].username/items[].name (Actor ID), items[].title, items[].stats.totalUsers30Days, items[].currentPricingInfo.pricingModel.

Step 2: Fetch Actor schema and check gotchas

Fetch the input schema dynamically:

apify actors info "ACTOR_ID" --input --json 2>/dev/null

Also read references/gotchas.md to check for common pitfalls for the selected Actor.

For Actor documentation: apify actors info "ACTOR_ID" --readme

Step 3: Configure and run

Skip user preferences for simple lookups (e.g., "Nike's follower count"). Go straight to running with quick answer mode.

For larger tasks, confirm output format (quick answer / CSV / JSON) and result count.

Standard run (blocking):

apify actors call "ACTOR_ID" -i 'JSON_INPUT' --json 2>/dev/null

From output: .id (run ID), .status, .defaultDatasetId, .stats.durationMillis

Fetch results:

apify datasets get-items DATASET_ID --format json

For CSV: apify datasets get-items DATASET_ID --format csv

Quick answer mode: Fetch results as JSON, pick top 5, present formatted in chat.

Save to file: Fetch results, use Write tool to save as YYYY-MM-DD_descriptive-name.csv or .json.

Large/long-running scrapes:

apify actors start "ACTOR_ID" -i 'JSON_INPUT' --json 2>/dev/null

Poll: apify runs info RUN_ID --json 2>/dev/null (check .status for SUCCEEDED).

Step 4: Deliver results

Report: result count, file location (if saved), key data fields, and links:

• Dataset: https://console.apify.com/storage/datasets/DATASET_ID
• Run: https://console.apify.com/actors/runs/RUN_ID

For multi-step workflows: suggest the next pipeline step from the workflow guide.

Troubleshooting

Common errors and pitfalls are documented in references/gotchas.md. Read it before running PPE (pay-per-event) Actors.