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Apify

Web automation and scraping platform with actors, datasets, APIs, and integrations for data extraction workflows.

by Apify·added 2026-04-27·
HarnessCLI
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Source URLs
https://docs.apify.com, https://github.com/JSONbored/awesome-claude/blob/main/content/tools/apify.mdx, https://apify.com
Brand
Apify
Brand domain
apify.com
Brand asset source
brandfetch
Author
Apify
Claim status
unclaimed
Last verified
2026-04-27

Schema details

Install type
copy
Troubleshooting
No
Tool listing metadata
Pricing
freemium
Disclosure
editorial
Application category
DeveloperApplication
Operating system
Web
Full copyable content
## Editorial notes

Apify is useful for agent builders who need reusable data extraction workflows, web automation actors, and hosted datasets.

## Disclosure

Editorial listing. No paid placement or affiliate link is used.

About this resource

Editorial notes

Apify is useful for agent builders who need reusable data extraction workflows, web automation actors, and hosted datasets.

Disclosure

Editorial listing. No paid placement or affiliate link is used.

Source citations

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How it compares

Apify side by side with 3 alternatives on trust, install, platform support, and disclosed safety notes — all from reviewed registry metadata.

Field

Web automation and scraping platform with actors, datasets, APIs, and integrations for data extraction workflows.

Open dossier

Open-source, self-hostable workflow automation platform with AI workflows, TypeScript pieces, human-in-the-loop steps, and a built-in MCP server.

Open dossier

Open-source browser automation library for building AI agents that can navigate, click, type, and inspect websites.

Open dossier

Open-source platform that runs Claude agents in isolated per-session containers, connects them to messaging channels, keeps per-agent memory and scheduled tasks, and routes credentials through a vault so keys never enter containers.

Open dossier
Trust
Install riskReview firstReview firstReview firstReview first
Notes Safety · Privacy · Safety Privacy Safety Privacy Safety Privacy
BrandApify logoApifyActivepieces logoActivepiecesBrowser Use logoBrowser UseNanoClaw logoNanoClaw
Categorytoolstoolstoolstools
Sourcesource-backedsource-backedsource-backedsource-backed
AuthorApifyActivepiecesBrowser Usenanocoai
Added2026-04-272026-06-032026-04-272026-06-05
Platforms
CLI
CLI
CLI
CLI
Source repo
Safety notes— missingActivepieces flows can send messages, call APIs, write records, publish webhooks, run code, and trigger cross-system side effects, so production flows need tests, approvals, rollback paths, and rate-limit controls. The built-in MCP server can let AI assistants build flows, manage tables, inspect runs, test automations, and publish changes; enable only the needed tool categories and keep project scope tight. Custom TypeScript pieces and code steps should be reviewed like application code, especially when they handle secrets, filesystem access, network calls, or business-critical integrations.Browser Use drives a real browser and can navigate, click, type, and submit forms autonomously; run it against trusted sites and review actions before granting access to logged-in sessions or sensitive accounts.Agents run in OS-level container isolation (Docker or Apple Container) with explicit filesystem mounts; bash commands execute inside containers, not on the host. Each agent group gets its own container, isolated CLAUDE.md memory, and selective mounts, limiting what a single agent can reach. Scheduled tasks run Claude on a recurring basis and can message users automatically; review schedules and message permissions. Messaging channels are installed on demand and can send outbound messages on your behalf, so scope which channels and agents are enabled.
Privacy notes— missingWorkflows can process prompts, customer records, emails, documents, form responses, table data, app payloads, webhooks, run logs, error traces, and AI-generated outputs. Activepieces connections may store OAuth tokens, API keys, account identifiers, webhook URLs, and service credentials; avoid exposing them in prompts, logs, MCP tool output, screenshots, or exported flows. Self-hosted deployments still need retention, backup, database, Redis, worker isolation, outbound network, telemetry, and access-control policies for all flow and run data.Page content, screenshots, and DOM data are sent to the configured LLM provider to plan actions, and agents can read and submit data on authenticated sites; control credentials and which pages agents can access.API keys never enter containers; outbound requests route through OneCLI's Agent Vault, which enforces per-agent policies and rate limits. Messages flow through inbound/outbound SQLite databases rather than shared memory, and each agent group only accesses explicitly mounted directories. Channels can be configured for full per-channel privacy, unified memory with separate conversations, or a single shared session; choose the mode that matches your privacy needs. Running Claude through the Anthropic Agent SDK sends conversation context to Anthropic's API.
Prerequisites— none listed
  • Activepieces Cloud account or reviewed self-hosted deployment using Docker, Docker Compose, Kubernetes, or another supported hosting path.
  • Connected app credentials, OAuth grants, webhooks, tables, and flow permissions scoped to the automations being built.
  • Review policy for which flows an AI assistant or MCP client may create, modify, publish, test, retry, or disable.
— none listed
  • macOS or Linux, or Windows via WSL2.
  • Node.js 20+ and pnpm 10+.
  • Docker Desktop or Engine (or Apple Container on macOS) for container isolation.
  • Claude Code for skills and customization, plus Anthropic Agent SDK access.
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