How to Use the Import.io (Web Data Extraction) MCP in OpenAI Agents SDK

Q: Can an agent check extraction status in OpenAI Agents SDK?

Yes, your agent uses getextractorstatus to poll active runs. It handles this asynchronously within the agent run loop to prevent blocking other tasks.

Q: How does Import.io (Web Data Extraction) handle large datasets in OpenAI Agents SDK?

The agent triggers getcrawldata or downloadcsv to pull structured data. This avoids sending raw HTML to the LLM, saving token costs.

Q: What is the best way to handle rate limits with this MCP Server?

Your agent should check accountusage before starting large crawl jobs. This keeps your consumption within budget limits.

Get raw web data directly into your OpenAI Agents SDK production pipelines without writing custom scrapers.

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Connect Import.io (Web Data Extraction) MCP to OpenAI Agents SDK

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

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Setup Import.io (Web Data Extraction) with OpenAI Agents SDK

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Run Web Extractors Directly From Your Agent Pipeline

Your OpenAI agent uses `run_extractor` to pull structured data from target web pages on demand. This tool lets the agent trigger the extraction process asynchronously and returns a tracking ID immediately. To avoid blocking the execution flow, the agent polls `get_extractor_status` until the job finishes. Once it confirms a successful run, the agent calls `get_extractor_data` to feed clean JSON back into your OpenAI Agents SDK run loop using this MCP Server.

Manage Bulk Crawls with OpenAI Agents SDK

The MCP Server exposes `start_crawl` to let your agent kick off large-scale, multi-page web extractions concurrently. That's the whole point—you don't have to write custom queue management or proxy rotation code in Python. Monitoring progress is simple: the agent polls `get_crawl_status` to track pages processed and success rates. When the crawl ends, the agent pulls down the complete dataset using `get_crawl_data` for immediate analysis or downstream handoffs.

Quick Data Scrapes and Resource Auditing

Your agent uses `run_magic_api` to quickly analyze unfamiliar web layouts without prior configuration. This tool handles the raw page rendering so your agent can inspect page structures on the fly. Before running heavy jobs, the agent checks `account_usage` to verify remaining credits. It can also pull structured tables as CSV text via `download_csv` to feed directly into spreadsheet processing steps.

Setup guide

Set up Import.io (Web Data Extraction) MCP in OpenAI Agents SDK

Prerequisites

Python 3.10+ installed
openai-agents package (pip install openai-agents)
Active Vinkius subscription with a valid endpoint token

1

Install the SDK

Run pip install openai-agents to install the OpenAI Agents SDK. The MCP integration is built-in — no extra dependencies needed.
2

Connect via SSE transport

Use MCPServerSse with your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. The SDK auto-discovers all Import.io (Web Data Extraction) tools at runtime.
3

Create your Agent

Pass the MCP to Agent(mcp_servers=[server]). The agent receives Import.io (Web Data Extraction) tools as native definitions — JSON schemas resolve automatically.
4

Run the agent

Call Runner.run(agent, prompt) to execute. The agent invokes the appropriate Import.io (Web Data Extraction) tools and returns structured results. Copy the full example on the right to get started.

agent.py

import asyncio
from agents import Agent, Runner
from agents.mcp import MCPServerSse

async def main():
    async with MCPServerSse(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ) as server:
        agent = Agent(
            name="Import.io (Web Data Extraction) Agent",
            instructions="You have access to Import.io (Web Data Extraction) tools.",
            mcp_servers=[server],
        )
        result = await Runner.run(agent, "List recent transactions")
        print(result.final_output)

asyncio.run(main())

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Common questions about Import.io (Web Data Extraction) MCP in OpenAI Agents SDK

You register the MCP Server endpoint using the streamable HTTP parameters. The SDK queries the server schema and exposes tools like `list_extractors` directly to your agent.

Yes, your agent uses `get_extractor_status` to poll active runs. It handles this asynchronously within the agent run loop to prevent blocking other tasks.

The agent triggers `get_crawl_data` or `download_csv` to pull structured data. This avoids sending raw HTML to the LLM, saving token costs.

Your agent should check `account_usage` before starting large crawl jobs. This keeps your consumption within budget limits.

Your API keys, target URLs, and extracted JSON payload run through an isolated environment. This MCP Server uses ephemeral V8 sandboxes to isolate execution, and Vinkius processes these requests without storing your extraction payloads or target credentials.

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