Apify

Executes serverless microapps (Actors) that extract structured data from social platforms (TikTok, Instagram, Facebook) by automating browser interactions, parsing DOM/API responses, and handling anti-scraping protections. Actors run in isolated cloud containers with configurable RAM (8GB-256GB) and return results to managed datasets. The platform abstracts away proxy rotation, session management, and rate-limit handling through built-in infrastructure.

Enables developers to write custom web scraping logic in JavaScript/Python using Apify SDK, deploy to serverless containers, and execute at scale with automatic proxy management, scheduling, and result storage. Developers write Actor code locally, push to Apify platform, and the runtime handles containerization, resource allocation (8GB-256GB RAM), concurrent execution (up to 256 runs on Enterprise), and dataset persistence. SDK provides abstractions for browser automation (Puppeteer/Playwright), HTTP requests, data parsing, and error handling.

Enforces input schema validation for Actors, ensuring parameters match expected types and constraints before execution. Developers define input schema (JSON Schema format) in Actor code, and Apify validates inputs against the schema before queuing the run. Invalid inputs are rejected with detailed error messages, preventing malformed runs and wasted compute units. The platform provides UI form generation from schema, enabling non-technical users to provide inputs without manual JSON construction.

Provides real-time execution logs, performance metrics, and error tracking for Actor runs. Developers view logs in Apify dashboard or via API, with filtering by log level (info, warning, error), timestamp, and custom tags. Metrics include execution time, RAM usage, CPU usage, and compute unit consumption. Failed runs include error stack traces and suggestions for debugging. The platform retains logs for a configurable period, enabling post-mortem analysis and performance optimization.

Command-line interface for local Actor development, testing, and deployment to Apify platform. Developers use `apify create` to scaffold new Actors, `apify run` to test locally, and `apify push` to deploy to the cloud. The CLI handles authentication, version management, and deployment orchestration. Local testing uses the same runtime as cloud execution, enabling accurate pre-deployment validation. The CLI integrates with Git for version control and supports environment variables for secrets management.

Enables developers to monetize custom Actors by publishing to the Apify marketplace with revenue sharing. Apify takes a percentage of Actor usage fees, and developers earn the remainder. Pricing is set by the developer (per compute unit or flat fee), and Apify handles billing and payment processing. Developers track revenue via dashboard and receive payouts monthly. The marketplace provides visibility and discoverability for monetized Actors.

Automatically rotates IP addresses across datacenter and residential proxy pools to bypass anti-scraping detection and rate limiting. The platform manages proxy selection, failure handling, and geographic routing transparently within Actor execution. Developers specify proxy type (datacenter, residential, or SERP) via Actor configuration, and Apify handles IP rotation, session persistence, and fallback logic without code changes. Residential proxies route through real user devices; datacenter proxies use fast data center IPs; SERP proxies are optimized for search engine scraping.

Triggers Actor execution on fixed schedules (hourly, daily, weekly, monthly) or via webhooks, storing results in managed datasets with automatic versioning. Developers define schedules via Apify UI or API, and the platform queues and executes Actors at specified times, handling retries on failure and persisting results. Results are accessible via dataset API, exportable to external systems, or forwarded via webhooks. Scheduling abstracts away cron job management and distributed task queuing.

Extracts and validates structured data from web pages using developer-defined schemas, automatically parsing HTML/JSON responses and mapping to typed output formats. Actors use schema definitions (JSON Schema or Apify-specific format) to validate extracted data, enforce type constraints, and handle missing fields. The platform provides schema-aware parsing utilities in the SDK, enabling developers to define extraction rules once and apply them across multiple pages or runs with consistent output structure.

Persists Actor results in managed cloud datasets with automatic versioning, enabling historical comparison and incremental updates. Each Actor run appends results to a dataset; Apify maintains version history, allowing queries across specific runs or date ranges. Datasets support JSON, CSV, and Parquet export formats. The platform provides dataset API for programmatic access, filtering, and pagination. Storage is billed per GB-hour, with tiered pricing based on subscription level. Developers can query datasets via API or export for external analysis.

Crawls websites, extracts text content in Markdown format, and cleans HTML to produce LLM-ready data. The Website Content Crawler Actor automatically follows internal links, extracts readable text, removes boilerplate (navigation, ads, footers), and outputs Markdown-formatted content. Results are optimized for feeding into LLM applications, RAG pipelines, and vector databases. The platform provides explicit integration with LangChain and LlamaIndex, enabling seamless data flow from web to LLM without intermediate processing.

Exposes Apify Actors as tools accessible to AI agents and LLMs via the Model Context Protocol (MCP) standard. The Apify MCP server allows LLMs to discover available Actors, invoke them with parameters, and receive results without direct API calls. Developers deploy the MCP server, configure Actor mappings, and LLMs can then call Actors as native tools within their reasoning loops. This enables AI agents to autonomously trigger web scraping tasks as part of multi-step workflows.

Provides a curated marketplace of 2,000+ pre-built Actors with search, filtering, and rating system. Developers browse Actors by category (social media, e-commerce, search engines), view documentation, test with sample inputs, and deploy with one click. The marketplace includes community-contributed Actors and official Apify Actors. Each Actor listing includes pricing (compute unit cost), input/output schema, and user reviews. Developers can fork Actors, customize them, and republish to the marketplace.

Manages concurrent execution of multiple Actors with tiered resource allocation (RAM, CPU) based on subscription level. Developers specify Actor RAM (8GB-256GB) and the platform queues runs, executing up to the concurrent limit (1 on Free, 256+ on Enterprise). The platform auto-scales container resources and handles job queuing without developer intervention. Billing is per compute unit (CU), with CU cost varying by plan tier ($0.20 on Free, $0.13 on Business). Developers can monitor execution status, logs, and resource usage via dashboard or API.