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Apify

Apify MCP Server

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Command Apify scrapers from your AI agent — run actors, extract web data, poll datasets, and automate browser tasks seamlessly.

Vinkius supports streamable HTTP and SSE.

AI AgentVinkius
High Security·Kill Switch·Plug and Play
Apify
Fully ManagedVinkius Servers
60%Token savings
High SecurityEnterprise-grade
IAMAccess control
EU AI ActCompliant
DLPData protection
V8 IsolateSandboxed
Ed25519Audit chain
<40msKill switch
Stream every event to Splunk, Datadog, or your own webhook in real-time

* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

What is the Apify MCP Server?

The Apify MCP Server gives AI agents like Claude, ChatGPT, and Cursor direct access to Apify via 10 tools. Command Apify scrapers from your AI agent — run actors, extract web data, poll datasets, and automate browser tasks seamlessly. Powered by the Vinkius - no API keys, no infrastructure, connect in under 2 minutes.

Built-in capabilities (10)

abort_runget_account_limitsget_dataset_itemsget_key_value_storeget_runlist_actorslist_webhookspush_to_queuerun_actorrun_actor_sync

Tools for your AI Agents to operate Apify

Ask your AI agent "List all the Apify actors available on my account." and get the answer without opening a single dashboard. With 10 tools connected to real Apify data, your agents reason over live information, cross-reference it with other MCP servers, and deliver insights you would spend hours assembling manually.

Works with Claude, ChatGPT, Cursor, and any MCP-compatible client. Powered by the Vinkius - your credentials never touch the AI model, every request is auditable. Connect in under two minutes.

Why teams choose Vinkius

One subscription gives you access to thousands of MCP servers - and you can deploy your own to the Vinkius Edge. Your AI agents only access the data you authorize, with DLP that blocks sensitive information from ever reaching the model, kill switch for instant shutdown, and up to 60% token savings. Enterprise-grade infrastructure and security, zero maintenance.

Build your own MCP Server with our secure development framework →

Vinkius works with every AI agent you already use

…and any MCP-compatible client

CursorClaudeOpenAIVS CodeCopilotGoogleLovableMistralAWSCursorClaudeOpenAIVS CodeCopilotGoogleLovableMistralAWS

Apify MCP Server capabilities

10 tools
abort_run

Any data already scraped and pushed to the dataset is preserved. The run status changes to ABORTED. Use this to stop runaway scrapes or when sufficient data has been collected. Graceful shutdown depends on the actor implementation. Abort an active Apify actor run

get_account_limits

Essential for monitoring consumption and avoiding overage charges. Check Apify account subscription limits and compute unit usage

get_dataset_items

The datasetId is found in the run object (defaultDatasetId). Supports pagination via limit (max items per page) and offset (starting position). Returns an array of JSON objects containing the scraped data fields. Use limit=1000 for bulk downloads. Export structured JSON data from an Apify dataset

get_key_value_store

Key-value stores hold arbitrary data like screenshots (OUTPUT), configuration files, or intermediate results. The storeId comes from the run object (defaultKeyValueStoreId). Common keys include "OUTPUT", "INPUT", and "SCREENSHOT". Retrieve an item from an Apify actor key-value store

get_run

Poll this endpoint to track long-running scrapes. Check the status and metadata of a specific Apify actor run

list_actors

Includes owned actors and those from the Apify Store that have been saved. Each entry contains the actorId, name, description, and default run configuration. Use the actorId to trigger runs. List all accessible actors in the Apify account

list_webhooks

RUN.SUCCEEDED, ACTOR.RUN.FAILED), target URLs, and associated actor IDs. Webhooks enable event-driven architectures by notifying external systems when actor runs complete or fail. List all configured webhooks in the Apify account

push_to_queue

Pass the queueId (from the run object) and a JSON string array of request objects, e.g., [{"url":"https://...","uniqueKey":"..."}]. This enables dynamic crawling where new pages are discovered and added during execution. Dynamically push new URLs to an active Apify request queue

run_actor

Pass the actorId (e.g., "apify/web-scraper" or a custom ID) and a JSON string with the input configuration (start URLs, proxy settings, max pages, etc.). Returns immediately with a runId. Use ap.get_run to poll for completion and ap.get_dataset_items to retrieve extracted data. Start an Apify actor asynchronously with custom JSON input

run_actor_sync

run_actor but waits for the actor to finish before returning. The response includes the full run object with defaultDatasetId for immediate data retrieval. Best for short-lived actors (under 5 minutes). For long-running scrapes, use the async ap.run_actor instead. Run an Apify actor and block until completion (synchronous)

What the Apify MCP Server unlocks

Connect your Apify workspace to your AI agent and seamlessly direct full-stack web scraping and data extraction workflows through natural conversation.

What you can do

  • Discover & Run Actors — Browse all scraper bots (Actors) available in your account. Fire them off asynchronously or synchronously for fast, targeted scraping
  • Extract Datasets — Pull robust structured data formats out of completed runs. Retrieve detailed JSON records directly into the agent's context window
  • Fetch Key-Value Stores — Programmatically read snapshots, cached HTML pages, or screenshots from the Apify Key-Value repositories mapped to a run
  • Job Control & Scalability — Stop hanging scraper jobs, queue new dynamic URLs mid-run, or inspect deep usage analytics, compute units, and webhooks limits

How it works

1. Subscribe to this server
2. Enter your Personal Apify API Token
3. Start exploring and interacting with data extraction routines securely via Claude or Cursor

Who is this for?

  • Data Engineers — trigger scheduled extraction logic seamlessly and map Apify objects within a conversational QA check
  • Market Researchers — command the AI to scrape product prices using Apify actors and compile the JSON datasets into readable markdown tables
  • AI Developers — augment your agent's real-time capabilities by feeding it massive structured site data freshly scraped via headless browsers

Frequently asked questions about the Apify MCP Server

01

How can the AI agent run a scrape on a list of product URLs?

First, find your specific scraping Actor ID via list_actors. Then, prompt your agent to execute run_actor, providing the target URLs formatted as a structured JSON input payload. It returns a 'Run ID'. You can poll this run via get_run, and once it succeeds, the agent calls get_dataset_items to pull all acquired data straight to your window.

02

Can the agent interact with run configurations mid-way during crawling?

Yes. If an Apify crawler is currently executing and utilizes a Request Queue, you can instruct your agent to call push_to_queue. Doing so dynamically ships new URLs to the active queue instance, extending the current web crawl without needing to stop or restart the Actor.

03

Can my AI automatically detect scraping timeouts and debug the failure?

Absolutely. Because your agent can track real execution flows with get_run, it's aware if it transitions to TIMED-OUT or FAILED states. Subsequently, you can ask the agent to examine the KV Store log outputs ensuring the underlying issue (e.g. captcha block, blocking proxy) is identified immediately.

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