Apify Connector for AI agents.
7 live capabilities
Run web scraping and data extraction tasks through your AI client.
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Why people use Apify
Apify Web Scraping for Automated Data Extraction
This Connector puts the power of Apify directly into your agent's hands. You just ask for the data, and the agent handles the execution, status checking, and result retrieval. You get the final answer without ever leaving your chat window.
What Vinkius changes
You can manage your entire web scraping pipeline through a simple chat interface.
Use it from Claude, ChatGPT, Cursor or another AI client you already have.
One account · 5,900+ Connectors
- Real-world use case 01
Quick price monitoring
A researcher needs to know the current price of 50 products.
- Real-world use case 02
Debugging failed scrapers
An engineer needs to check why a scraper failed.
- Real-world use case 03
Summarizing customer reviews
A PM wants a summary of recent reviews.
Complete set · 7capabilities
The complete Apify capability set.
These are the exact actions your AI can choose when you ask it to work with Apify.
01—04
4 capabilities in this set.
Part of 7 available through Apify.
- 01 Capability
Get dataset results
Pulls specific items from a dataset so your agent can read and analyze them. It makes it easy to get data into your conversation.
- 02 Capability
Get run details
Shows the status and metadata for a specific actor execution. This helps you debug your scrapers quickly.
- 03 Capability
List actors
Shows all the scraping actors available in your account. Use this to see what capabilities you can trigger.
- 04 Capability
List actor runs
Lists recent executions to help you track your scraping history. It lets you see what finished and what failed.
05—07
3 capabilities in this set.
Part of 7 available through Apify.
- 05 Capability
List actor tasks
Shows your saved actor configurations for easy reuse. It helps you avoid retyping the same settings every time.
- 06 Capability
List datasets
Lists all the datasets in your account. This gives you a clear view of all your collected data.
- 07 Capability
Run actor
Starts a new scraper run with your specific input parameters. This lets you trigger a scrape directly from your chat.
Set up in minutes
One URL. Then ask Apify to work.
Claude and ChatGPT only need the Connector URL. Copy it once, add it in settings, and use Apify from the conversation.
Choose your client
Live previewAdvanced clients IDE · CLI
Claude · Web + desktop
Connector URL · ready to paste
Streamable HTTPhttps://edge.vinkius.com/vk_preview_XpiRRgIukBoSRPKSbj93XBldWyxkE1Ba9k2he2x5/mcp - Step 01
Open Connectors
In Claude Web or Claude Desktop, open Settings and choose Connectors.
- Step 02
Add the URL
Choose Add custom connector, name it Apify, and paste the URL above.
- Step 03
Turn it on in chat
Select +, open Connectors, and enable Apify for the conversation.
ChatGPT · Web + desktop
Connector URL · ready to paste
Streamable HTTPhttps://edge.vinkius.com/vk_preview_XpiRRgIukBoSRPKSbj93XBldWyxkE1Ba9k2he2x5/mcp - Step 01
Open MCP settings
On desktop, open Settings and MCP servers. On web, open your workspace app or connector settings.
- Step 02
Add the URL
Choose Add server with Streamable HTTP, or create a custom MCP app, then paste the Apify URL.
- Step 03
Save and start
Save the connection and enable Apify in your conversation. Desktop may ask you to restart once.
Cursor · IDE configuration
Advanced setup
{
"mcpServers": {
"apify-extended": {
"url": "https://edge.vinkius.com/vk_preview_XpiRRgIukBoSRPKSbj93XBldWyxkE1Ba9k2he2x5/mcp"
}
}
} - Step 01
Open MCP Settings
Press Cmd+Shift+P (macOS) or Ctrl+Shift+P (Windows/Linux) → search "MCP Settings"
- Step 02
Add the server config
Paste the JSON configuration above into the mcp.json file that opens
- Step 03
Save the file
Cursor will automatically detect the new Connector
- Step 04
Start using Apify
Open Agent mode in chat and ask: "Using Apify, help me...". 7 tools available
VS Code Copilot · IDE configuration
Advanced setup
{
"mcpServers": {
"apify-extended": {
"url": "https://edge.vinkius.com/vk_preview_XpiRRgIukBoSRPKSbj93XBldWyxkE1Ba9k2he2x5/mcp"
}
}
} - Step 01
Create MCP config
Create a .vscode/mcp.json file in your project root
- Step 02
Add the server config
Paste the JSON configuration above
- Step 03
Enable Agent mode
Open GitHub Copilot Chat and switch to Agent mode using the dropdown
- Step 04
Start using Apify
Ask Copilot: "Using Apify, help me...". 7 tools available
Windsurf · IDE configuration
Advanced setup
{
"mcpServers": {
"apify-extended": {
"url": "https://edge.vinkius.com/vk_preview_XpiRRgIukBoSRPKSbj93XBldWyxkE1Ba9k2he2x5/mcp"
}
}
} - Step 01
Open MCP Settings
Go to Settings → MCP Configuration or press Cmd+Shift+P and search "MCP"
- Step 02
Add the server
Paste the JSON configuration above into mcp_config.json
- Step 03
Save and reload
Windsurf will detect the new server automatically
- Step 04
Start using Apify
Open Cascade and ask: "Using Apify, help me...". 7 tools available
Cline · IDE configuration
Advanced setup
{
"mcpServers": {
"apify-extended": {
"url": "https://edge.vinkius.com/vk_preview_XpiRRgIukBoSRPKSbj93XBldWyxkE1Ba9k2he2x5/mcp"
}
}
} - Step 01
Open Cline MCP Settings
Click the Connectors icon in the Cline sidebar panel
- Step 02
Add remote server
Click "Add Connector" and paste the configuration above
- Step 03
Enable the server
Toggle the server switch to ON
- Step 04
Start using Apify
Ask Cline: "Using Apify, help me...". 7 tools available
Claude Code · Terminal command
Advanced setup
claude mcp add apify-extended --transport http "https://edge.vinkius.com/vk_preview_XpiRRgIukBoSRPKSbj93XBldWyxkE1Ba9k2he2x5/mcp" - Step 01
Install Claude Code
Run npm install -g @anthropic-ai/claude-code if not already installed
- Step 02
Add the Connector
Run the command above in your terminal
- Step 03
Verify the connection
Run claude mcp to list connected servers, or type /mcp inside a session
- Step 04
Start using Apify
Ask Claude: "Using Apify, show me...". 7 tools are ready
Where the request belongs
Work Apify can move forward.
Data engineers tired of manual scraping, researchers needing bulk web data, and product managers who want real-time data updates without touching a dashboard.
Data Scientist
Pulls scraped records into a chat to find trends without exporting files to a spreadsheet.
Automation Engineer
Triggers and monitors actor runs to ensure scrapers stay healthy and active.
Product Manager
Gets quick summaries of scraped datasets to inform product decisions without manual data handling.
Build the capability set
Add more capabilities.
Each Connector adds new actions and data without changing how you work.
Browse ConnectorsApify
Run web scraping actors, collect structured data, and manage storage datasets for large-scale data extraction projects.
Browse AI
Automate web scraping with Browse AI. run extraction robots, monitor page changes, and retrieve bulk data directly from any AI agent.
Grepsr
Automate web scraping via Grepsr. manage reports, trigger crawls, and retrieve data directly via AI.
Olostep
Scrape web pages at scale with a headless browser API that renders JavaScript and returns clean structured data instantly.
ParseHub
Control advanced cloud scraping projects via ParseHub. list targets, dispatch headless runs, trace crawler status, and fetch extracted datasets directly via AI.
Nimbleway
Web data collection and scraping via Nimbleway. extract content and search the web directly from your AI agent.
Bring your own AI
Change the model, client or framework. Keep Apify connected.
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Claude -
ChatGPT -
Gemini -
Cursor -
VS Code -
Windsurf -
ZCode -
Cline -
Zed -
Continue -
Kiro -
Roo Code -
Zencoder -
Goose -
Void -
Augment Code -
Amp -
Qodo -
Tabnine -
Pieces -
Sourcegraph Cody -
JetBrains -
Warp -
Amazon Q -
Antigravity -
BoltAI -
Raycast -
Jan -
LM Studio -
AnythingLLM -
Open WebUI -
Msty -
Cherry Studio -
LibreChat -
TypingMind -
Chorus -
5ire -
n8n -
LangChain -
LlamaIndex -
CrewAI -
Vercel AI SDK
Before you connect
Questions about Apify.
The practical details behind the request, access and result.
Can the Apify MCP run scrapers for me?
Yes, it triggers actors directly. This means you can start a web scraping job just by asking your agent to do it.
How do I get my scraped data into my AI?
The Connector pulls results from your datasets. Your agent can then read those records and summarize them for you immediately.
Can I see if my scraper failed?
Yes, you can check your scraping history. The agent can look at recent executions to see if they finished successfully.
Does this work with my existing Apify account?
Yes, you just need to provide your API token. It connects your current account to any MCP-compatible client.
Can I manage multiple datasets?
Yes, the Connector lists all your datasets. This makes it easy to switch between different data collections in one chat.
Is this good for large scale data extraction?
Yes, it's built for that. It handles the management of actors and datasets so you can focus on the results.
How do I reuse old scraper settings?
You can list your saved tasks. This lets your agent find a previous configuration and run it again with new inputs.
Can I provide input parameters when running an actor?
Yes! Use the run_actor capability and provide the optional input JSON object to configure specific scraper settings for that run.
How do I see the items collected in a dataset?
Run the get_dataset_results query with your Dataset ID. The agent will retrieve the data records, which you can then ask the AI to summarize or analyze.
Is it possible to check the status of a specific actor run?
Absolutely. Use the get_run_details capability and provide the Run ID. Your agent will retrieve the status (RUNNING, SUCCEEDED, FAILED) and metadata for that specific execution.
One connection away
Give your agent a direct line to Apify.
Connect Apify once. Keep it beside 5,900+ managed Connectors when the next task needs more.
Explore every Connector No credit card required · Free tier available