WebScrapingAPI MCP Server for OpenAI Agents SDK 10 tools — connect in under 2 minutes
The OpenAI Agents SDK enables production-grade agent workflows in Python. Connect WebScrapingAPI through the Vinkius and your agents gain typed, auto-discovered tools with built-in guardrails — no manual schema definitions required.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
import asyncio
from agents import Agent, Runner
from agents.mcp import MCPServerStreamableHttp
async def main():
# Your Vinkius token — get it at cloud.vinkius.com
async with MCPServerStreamableHttp(
url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
) as mcp_server:
agent = Agent(
name="WebScrapingAPI Assistant",
instructions=(
"You help users interact with WebScrapingAPI. "
"You have access to 10 tools."
),
mcp_servers=[mcp_server],
)
result = await Runner.run(
agent, "List all available tools from WebScrapingAPI"
)
print(result.final_output)
asyncio.run(main())
* 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 WebScrapingAPI MCP Server
Connect your WebScrapingAPI account to any AI agent and harness the power of industrial-grade web scraping through natural conversation.
The OpenAI Agents SDK auto-discovers all 10 tools from WebScrapingAPI through native MCP integration. Build agents with built-in guardrails, tracing, and handoff patterns — chain multiple agents where one queries WebScrapingAPI, another analyzes results, and a third generates reports, all orchestrated through the Vinkius.
What you can do
- Universal Scraping — Retrieve raw HTML from any website using a massive network of datacenter and residential proxies to avoid blocks
- JavaScript Rendering — Scrape complex SPAs and dynamic pages by using a headless browser to capture the full rendered state
- SERP Discovery — Retrieve structured search engine results (organic, ads, snippets) from Google, Bing, and Yandex
- E-commerce Extraction — Scrape product details like price, reviews, and titles from major stores like Amazon and Walmart into structured JSON
- Anonymity & Bypass — Use residential or mobile proxies for high-anonymity scraping and to bypass even the most aggressive bot detections
- Auto-Parsing — Automatically extract structured data from news articles or product pages without manual selectors
- Custom Parameters — Execute scrapes with advanced options like geo-targeting, sessions, and custom headers
The WebScrapingAPI MCP Server exposes 10 tools through the Vinkius. Connect it to OpenAI Agents SDK 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 WebScrapingAPI to OpenAI Agents SDK via MCP
Follow these steps to integrate the WebScrapingAPI MCP Server with OpenAI Agents SDK.
Install the SDK
Run pip install openai-agents in your Python environment
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com
Run the script
Save the code above and run it: python agent.py
Explore tools
The agent will automatically discover 10 tools from WebScrapingAPI
Why Use OpenAI Agents SDK with the WebScrapingAPI MCP Server
OpenAI Agents SDK provides unique advantages when paired with WebScrapingAPI through the Model Context Protocol.
Native MCP integration via `MCPServerSse` — pass the URL and the SDK auto-discovers all tools with full type safety
Built-in guardrails, tracing, and handoff patterns let you build production-grade agents without reinventing safety infrastructure
Lightweight and composable: chain multiple agents and MCP servers in a single pipeline with minimal boilerplate
First-party OpenAI support ensures optimal compatibility with GPT models for tool calling and structured output
WebScrapingAPI + OpenAI Agents SDK Use Cases
Practical scenarios where OpenAI Agents SDK combined with the WebScrapingAPI MCP Server delivers measurable value.
Automated workflows: build agents that query WebScrapingAPI, process the data, and trigger follow-up actions autonomously
Multi-agent orchestration: create specialist agents — one queries WebScrapingAPI, another analyzes results, a third generates reports
Data enrichment pipelines: stream data through WebScrapingAPI tools and transform it with OpenAI models in a single async loop
Customer support bots: agents query WebScrapingAPI to resolve tickets, look up records, and update statuses without human intervention
WebScrapingAPI MCP Tools for OpenAI Agents SDK (10)
These 10 tools become available when you connect WebScrapingAPI to OpenAI Agents SDK via MCP:
custom_api_scrape
g. country, session, wait_for). Execute a scrape using advanced custom parameters
scrape_and_auto_extract
g. for news or product pages). Scrape with automatic structured data extraction
scrape_as_mobile
Scrape as a mobile device using WebScrapingAPI device emulation
scrape_ecommerce_product
Returns price, title, and reviews as structured JSON. Scrape product details from Amazon, Walmart, or other supported stores
scrape_js_rendered
Slower but captures the full rendered state. Scrape JS-rendered HTML using WebScrapingAPI headless browser
scrape_static_html
Pass the full target URL. Scrape raw HTML from any URL using WebScrapingAPI datacenter proxies
scrape_via_residential_proxy
Scrape using residential proxies for high anonymity and bypass
search_bing_serp
Retrieve structured search engine results from Bing
search_google_serp
Provide a query string. Retrieve structured search engine results from Google
search_yandex_serp
Retrieve structured search engine results from Yandex
Example Prompts for WebScrapingAPI in OpenAI Agents SDK
Ready-to-use prompts you can give your OpenAI Agents SDK agent to start working with WebScrapingAPI immediately.
"Scrape the rendered HTML of 'https://example.com/dynamic-dashboard'."
"Search Google for 'best wireless noise cancelling headphones' and return structured results."
"Get the price and rating for the product at 'https://amazon.com/dp/B09XXX'."
Troubleshooting WebScrapingAPI MCP Server with OpenAI Agents SDK
Common issues when connecting WebScrapingAPI to OpenAI Agents SDK through the Vinkius, and how to resolve them.
MCPServerStreamableHttp not found
pip install --upgrade openai-agentsAgent not calling tools
WebScrapingAPI + OpenAI Agents SDK FAQ
Common questions about integrating WebScrapingAPI MCP Server with OpenAI Agents SDK.
How does the OpenAI Agents SDK connect to MCP?
MCPServerSse(url=...) to create a server connection. The SDK auto-discovers all tools and makes them available to your agent with full type information.Can I use multiple MCP servers in one agent?
MCPServerSse instances to the agent constructor. The agent can use tools from all connected servers within a single run.Does the SDK support streaming responses?
Connect WebScrapingAPI with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect WebScrapingAPI to OpenAI Agents SDK
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.