Apify Integrations Hub: Connect Web Data to Your Stack
Apify is both a scraper runtime and a data integration layer. Finished datasets can flow into spreadsheets, warehouses, chat alerts, or LLM pipelines. This hub lists the main integration surfaces, with a single reference table you can scan before diving into deeper guides.
Quick Answer
Apify integrates with n8n, Make, Zapier, Google Sheets, Slack, LangChain, LlamaIndex, Airbyte, AWS S3, and more. All integrations use the Apify REST API or webhooks as the backbone.
No matter which app you connect, the pattern is the same: start a run → read the dataset or key-value store → push data to the destination (or let the destination pull via API). Sign up for Apify and open the Integrations directory on Apify Docs for the latest official list.
Three-step mental model
- Trigger: manual start, schedule, API call, or automation platform.
- Fetch: read items from the run's dataset (JSON/CSV export or paginated API).
- Deliver: POST to your app, sync to a sheet, upload to S3, or let a partner connector poll Apify.
Integration directory (quick reference)
| Integration | Category | What it does | Link |
|---|---|---|---|
| n8n | Automation | Native community node; trigger flows on run events, pull datasets | Apify + n8n guide |
| Make | Automation | Visual scenarios; branch on success/failure; map dataset fields | Apify + Make guide |
| Zapier | Automation | Zaps across 6,000+ apps when Actors finish | Apify + Zapier guide · Official Zapier docs |
| Google Sheets | Data export | Append or replace rows from datasets via Actor | Google Sheets guide |
| Slack | Notifications | Channel alerts for run lifecycle | Apify + Slack guide |
| Google Drive | Storage | Upload dataset files on completion | Google Drive guide |
| Gmail | Notifications | Email when runs succeed or fail | Integrations hub |
| GitHub | DevOps | CI/CD triggers and automation tied to Actor builds/runs | Apify + GitHub CI/CD |
| Airtable | Database | Push structured records to bases | Airtable integration |
| Airbyte | ETL / warehouse | Sync Apify datasets into warehouses and BI tools | Airbyte guide |
| Keboola | Data platform | Apify as a component in managed pipelines | Keboola integration |
| AWS S3 | Cloud storage | Export datasets to buckets (Actor or code) | S3 guide |
| LangChain | AI / LLM | Document loaders and tools over Apify datasets | LangChain guide |
| LlamaIndex | AI / RAG | Data connectors for retrieval pipelines | LlamaIndex docs |
| Haystack | AI / search | Retrieval components with web data | Haystack integration |
| MCP (Model Context Protocol) | AI agents | Let assistants list and run Actors | MCP docs · Use MCP servers |
| AI agents | AI agents | Give CrewAI, AutoGPT, and assistants live web tools | AI agent integrations |
| Pinecone / Qdrant / Milvus | Vector DB | Push chunks/embeddings for semantic search | Vector integrations |
| Telegram | Notifications | Alerts via Zapier or bots | Telegram integration |
| IFTTT | Automation | Simple cross-app triggers | IFTTT integration |
| Kestra | Orchestration | Data orchestration for complex ETL | Kestra integration |
| Gumloop | AI workflows | AI-native automation builder | Gumloop integration |
| Webhooks | Developer | HTTP callbacks on run/build events | Webhook docs |
| Monitoring & alerts | Developer | Track run health, errors, and uptime across Actors | Advanced Actor monitoring |
| REST API | Developer | Full platform control (runs, storage, schedules) | API tutorial · API reference |
| JavaScript SDK | Developer | apify-client for Node/TypeScript | API client |
| Python SDK | Developer | apify-client for Python services | API client |
| Actor chaining | Platform | Tasks, saved inputs, integrations tab between Actors | Actors & tasks |
No-code platforms in one sentence each
- Make: best when you want visual branching and rich JSON mapping without hosting automation yourself.
- Zapier: best when you need the widest app directory and the fastest one-to-one automations.
- n8n: best when you want self-hosted workflows, Git-backed flows, or tight infra control.
All three ultimately call the same Apify primitives: token auth, run Actors, read datasets.
Webhooks (event backbone)
Webhooks are how SaaS products and custom backends react the moment a run succeeds, fails, or times out. Configure them in the Apify Console or via API.
Common events include ACTOR.RUN.SUCCEEDED, ACTOR.RUN.FAILED, ACTOR.RUN.ABORTED, and ACTOR.RUN.TIMED_OUT. Payloads include identifiers you need to fetch results, such as defaultDatasetId. Failed deliveries are retried several times with exponential backoff. See the webhook event catalog.
REST API and SDKs
The Apify API v2 exposes everything available in the Console: run Actors with JSON input, page through dataset items, manage key-value stores and request queues, and configure schedules.
Official clients
| Language | Package | Install |
|---|---|---|
| JavaScript / TypeScript | apify-client | npm install apify-client |
| Python | apify-client | pip install apify-client |
Both clients handle retries and pagination helpers, ideal when your "integration" is a service you host.
AI and data pipelines
For RAG, agents, or batch enrichment, combine Apify Actors (scraping) with vector stores or orchestration frameworks. LangChain and LlamaIndex are the most common entry points; MCP is the fastest way to give Claude-class clients tool access to the Store.
Partner builders can also follow Integrate with Apify for OAuth and marketplace flows.
Choosing the right path
| Scenario | Start here |
|---|---|
| "Push rows to a spreadsheet automatically" | Google Sheets guide |
| "Notify my team in Slack" | Apify + Slack guide |
| "Trigger my own API when scraping finishes" | Webhooks |
| "Visual automation with minimal code" | Make or Zapier |
| "Self-hosted automation" | n8n |
| "Custom product embedding Apify" | REST API + OAuth docs |
| "Feed an LLM with fresh web data" | LangChain or MCP |
| "Give an AI agent live web tools" | AI agent integrations |
| "Watch Actor health and get failure alerts" | Advanced Actor monitoring |
Browse Actors, run a test scrape, and wire the dataset to your favorite tool. Get started on Apify.
Use no-code platforms (Make, n8n, Zapier), built-in Console integrations (Slack, Drive, Airtable), the Google Sheets Actor, webhooks to your own HTTP endpoint, or the REST API / official SDKs. Everything ultimately uses Apify APIs or webhooks.
Yes. Even Zapier connectors and n8n nodes wrap the same REST endpoints. Webhooks are the standard way to notify external systems when runs finish.
Yes. LangChain has documented loaders and tools; LlamaIndex lists Apify connectors for RAG pipelines. Pair them with vector databases such as Pinecone, Qdrant, or Milvus when you need semantic search.
Yes. Use the S3 Uploader Actor, Actor-to-Actor integrations, or the AWS SDK from your own code. See the dedicated S3 guide for IAM permissions and bucket patterns.
Actor run events cover created, succeeded, failed, aborted, timed out, and resurrected states; build events exist for Actor versions. Payloads include resource metadata so you can fetch datasets without guessing IDs.
Use the Airbyte connector documentation to sync Apify datasets into your warehouse. Keboola offers a similar managed path. Both treat Apify as a repeatable data source.
On Apify Docs under MCP integrations, and locally under use-mcp-servers for how to run MCP-ready Actors from AI clients such as Claude Desktop.
Pick Make for visual branching and rich JSON mapping, Zapier for the widest app directory and quick one-to-one automations, and n8n when you want self-hosted, Git-backed workflows you fully control. All three call the same Apify run-and-read-dataset primitives, so the choice is about hosting and ecosystem, not capability.
The Google Sheets integration appends or replaces dataset rows inside a spreadsheet so the data stays queryable. The Google Drive integration uploads exported dataset files (JSON, CSV, XLSX) as documents on completion. Use Sheets for live tabular data and Drive for file delivery and archiving.
Use webhooks for run lifecycle events, the REST API for run status, and Apify monitoring features for error rates, uptime, and alerting across Actors. The advanced Actor monitoring guide covers thresholds and notification channels.
Common mistakes and fixes
Webhook never hits my server
Confirm the URL is public HTTPS, returns 2xx within 30 seconds, and check Apify webhook delivery logs. Allowlist Apify static IPs if a firewall blocks inbound traffic.
Integration shows empty dataset
Wait for ACTOR.RUN.SUCCEEDED, pass defaultDatasetId from the webhook payload or API, and paginate dataset reads. Large runs are not a single response body.
Zapier or Make stops after Apify rate limits
Batch requests, use exponential backoff, and follow Apify API rate-limit headers. Upgrade plan or spread runs over time if you burst thousands of API calls.
