How to Use the Import.io (Web Data Extraction) MCP in AutoGen

Q: Can an AutoGen agent autonomously decide to run a bulk crawl using Import.io (Web Data Extraction)?

Yes, the lead agent can call startcrawl when it determines a task requires multi-page data. It coordinates with other agents to monitor the progress using getcrawlstatus.

Q: How do AutoGen agents handle failed web extractions from Import.io (Web Data Extraction)?

If getextractorstatus returns a failed state, the executing agent reports this to the group. The planner agent then decides whether to run runmagicapi as a fallback or try a different URL.

Q: How does the downloadcsv tool fit into a multi-agent workflow?

The data-processing agent calls downloadcsv to grab the raw spreadsheet text. It then passes this structured text to a code-execution agent for local analysis and plotting.

Deploy multi-agent debates to validate, execute, and monitor complex Import.io (Web Data Extraction) tasks in AutoGen using MCP.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect Import.io (Web Data Extraction) MCP to AutoGen

Create your Vinkius account to connect Import.io (Web Data Extraction) to AutoGen and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

GDPR Free for Subscribers

Setup Import.io (Web Data Extraction) with AutoGen

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Coordinate web extraction tasks across AutoGen agents

The `run_extractor` tool is triggered only after your planning agent and security agent agree on the target URL. AutoGen manages this negotiation to ensure your scraping tasks comply with internal policies. A dedicated monitoring agent polls `get_extractor_status` to watch the progress of the run. This separate agent alerts the group if a run fails, allowing the planner to try an alternative URL.

Let agents manage bulk crawls via this MCP Server

The `start_crawl` tool allows your lead agent to kick off high-volume scraping jobs across multiple web domains. While the crawl runs, a secondary validation agent checks `get_crawl_status` at regular intervals. When the crawl is complete, the validation agent uses `get_crawl_data` to inspect the results. If the data quality meets the defined threshold, the agent passes the clean JSON to the storage agent.

Audit credit usage and execute unstructured fallbacks

The `account_usage` tool is checked by your finance agent before any large-scale crawl is authorized. This MCP integration prevents your multi-agent system from running up unexpected API bills during autonomous runs. If a standard extractor fails, the group can vote to run `run_magic_api` to attempt unstructured extraction. This collaborative decision-making process ensures high success rates without human intervention.

Setup guide

Set up Import.io (Web Data Extraction) MCP in AutoGen

Prerequisites

Python 3.10+ installed
autogen-ext[mcp] package
Active Vinkius subscription with a valid endpoint token

1

Install AutoGen with MCP
Run pip install "autogen-ext[mcp]" autogen-agentchat. The MCP extension includes mcp_server_tools for stateless tool access.
2

Fetch tools from the MCP
Call mcp_server_tools(SseServerParams(url=...)) with your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Run your agent
Pass the tools to AssistantAgent and call agent.run(). The agent invokes Import.io (Web Data Extraction) tools and returns structured results.

agent.py

from autogen_ext.tools.mcp import SseServerParams, mcp_server_tools
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

server_params = SseServerParams(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

tools = await mcp_server_tools(server_params)

agent = AssistantAgent(
    name="Import.io (Web Data Extraction)_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent Import.io (Web Data Extraction) data")
print(result.messages[-1].content)

Get your connection token →

Prerequisites

Python 3.10+ installed
autogen-ext[mcp] + autogen-agentchat
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Same packages as above. McpWorkbench is ideal when your agent needs stateful sessions across multiple tool calls.
2

Use McpWorkbench as context manager
Wrap your agent in async with McpWorkbench(...) to maintain shared state and resources. The workbench manages the full MCP session lifecycle.
3

Run with workbench
Pass workbench=workbench to your agent. State is preserved across multiple tool calls within the same session.

agent.py

from autogen_ext.tools.mcp import McpWorkbench, SseServerParams
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

server_params = SseServerParams(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

async with McpWorkbench(server_params) as workbench:
    agent = AssistantAgent(
        name="Import.io (Web Data Extraction)_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent Import.io (Web Data Extraction) data")
    print(result.messages[-1].content)

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Import.io. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

Why Choose Vinkius

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

Connect Import.io (Web Data Extraction) now

Real-time monitoring

Live

visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about Import.io (Web Data Extraction) MCP in AutoGen

Your agents use McpToolAdapter to register the tools. One agent can trigger `run_extractor` while another polls `get_extractor_status` and a third processes the final `get_extractor_data` payload.

Yes, the lead agent can call `start_crawl` when it determines a task requires multi-page data. It coordinates with other agents to monitor the progress using `get_crawl_status`.

If `get_extractor_status` returns a failed state, the executing agent reports this to the group. The planner agent then decides whether to run `run_magic_api` as a fallback or try a different URL.

The data-processing agent calls `download_csv` to grab the raw spreadsheet text. It then passes this structured text to a code-execution agent for local analysis and plotting.

We isolate all API transactions inside secure V8 containers. Your API credentials never enter the LLM prompt context, protecting your account from prompt injection leaks.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python

Vercel AI SDK sdk-typescript