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.

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.

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.

Apify MCP Server for AutoGen 10 tools — connect in under 2 minutes

Name: Apify
Availability: InStock
Author: Vinkius

microsoft.github.io/autogen/docs/tools/mcp-tools

Built by Vinkius GDPR 10 Tools Framework

Microsoft AutoGen enables multi-agent conversations where agents negotiate, delegate, and execute tasks collaboratively. Add Apify as an MCP tool provider through Vinkius and every agent in the group can access live data and take action.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

import asyncio
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.tools.mcp import McpWorkbench

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    async with McpWorkbench(
        server_params={"url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"},
        transport="streamable_http",
    ) as workbench:
        tools = await workbench.list_tools()
        agent = AssistantAgent(
            name="apify_agent",
            tools=tools,
            system_message=(
                "You help users with Apify. "
                "10 tools available."
            ),
        )
        print(f"Agent ready with {len(tools)} tools")

asyncio.run(main())

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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

About Apify MCP Server

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

AutoGen enables multi-agent conversations where agents negotiate, delegate, and collaboratively use Apify tools. Connect 10 tools through Vinkius and assign role-based access. a data analyst queries while a reviewer validates, with optional human-in-the-loop approval for sensitive operations.

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

The Apify MCP Server exposes 10 tools through the Vinkius. Connect it to AutoGen in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect Apify to AutoGen via MCP

Follow these steps to integrate the Apify MCP Server with AutoGen.

Install AutoGen

Run pip install "autogen-ext[mcp]"

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Integrate into workflow

Use the agent in your AutoGen multi-agent orchestration

Explore tools

The workbench discovers 10 tools from Apify automatically

Why Use AutoGen with the Apify MCP Server

AutoGen provides unique advantages when paired with Apify through the Model Context Protocol.

Multi-agent conversations: multiple AutoGen agents discuss, delegate, and collaboratively use Apify tools to solve complex tasks

Role-based architecture lets you assign Apify tool access to specific agents. a data analyst queries while a reviewer validates

Human-in-the-loop support: agents can pause for human approval before executing sensitive Apify tool calls

Code execution sandbox: AutoGen agents can write and run code that processes Apify tool responses in an isolated environment

Apify + AutoGen Use Cases

Practical scenarios where AutoGen combined with the Apify MCP Server delivers measurable value.

Collaborative analysis: one agent queries Apify while another validates results and a third generates the final report

Automated review pipelines: a researcher agent fetches data from Apify, a critic agent evaluates quality, and a writer produces the output

Interactive planning: agents negotiate task allocation using Apify data to make informed decisions about resource distribution

Code generation with live data: an AutoGen coder agent writes scripts that process Apify responses in a sandboxed execution environment

Apify MCP Tools for AutoGen (10)

These 10 tools become available when you connect Apify to AutoGen via MCP:

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)

Example Prompts for Apify in AutoGen

Ready-to-use prompts you can give your AutoGen agent to start working with Apify immediately.

"List all the Apify actors available on my account."

"Verify the status of run 'qKpwH9LgC3r0Xm' and show me its final dataset if finished."

"How are our compute usage limits tracking this current month on Apify?"

Troubleshooting Apify MCP Server with AutoGen

Common issues when connecting Apify to AutoGen through the Vinkius, and how to resolve them.

McpWorkbench not found

Install: pip install "autogen-ext[mcp]"

Apify + AutoGen FAQ

Common questions about integrating Apify MCP Server with AutoGen.

How does AutoGen connect to MCP servers?

Create an MCP tool adapter and assign it to one or more agents in the group chat. AutoGen agents can then call Apify tools during their conversation turns.

Can different agents have different MCP tool access?

Yes. AutoGen's role-based architecture lets you assign specific MCP tools to specific agents, so a querying agent has different capabilities than a reviewing agent.