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WebScrapingAPI MCP Server for Vercel AI SDK 10 tools — connect in under 2 minutes

Built by Vinkius GDPR 10 Tools SDK

The Vercel AI SDK is the TypeScript toolkit for building AI-powered applications. Connect WebScrapingAPI through Vinkius and every tool is available as a typed function. ready for React Server Components, API routes, or any Node.js backend.

Vinkius supports streamable HTTP and SSE.

typescript
import { createMCPClient } from "@ai-sdk/mcp";
import { generateText } from "ai";
import { openai } from "@ai-sdk/openai";

async function main() {
  const mcpClient = await createMCPClient({
    transport: {
      type: "http",
      // Your Vinkius token. get it at cloud.vinkius.com
      url: "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
    },
  });

  try {
    const tools = await mcpClient.tools();
    const { text } = await generateText({
      model: openai("gpt-4o"),
      tools,
      prompt: "Using WebScrapingAPI, list all available capabilities.",
    });
    console.log(text);
  } finally {
    await mcpClient.close();
  }
}

main();
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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 Vercel AI SDK gives every WebScrapingAPI tool full TypeScript type inference, IDE autocomplete, and compile-time error checking. Connect 10 tools through Vinkius and stream results progressively to React, Svelte, or Vue components. works on Edge Functions, Cloudflare Workers, and any Node.js runtime.

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 Vercel AI 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 Vercel AI SDK via MCP

Follow these steps to integrate the WebScrapingAPI MCP Server with Vercel AI SDK.

01

Install dependencies

Run npm install @ai-sdk/mcp ai @ai-sdk/openai

02

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

03

Run the script

Save to agent.ts and run with npx tsx agent.ts

04

Explore tools

The SDK discovers 10 tools from WebScrapingAPI and passes them to the LLM

Why Use Vercel AI SDK with the WebScrapingAPI MCP Server

Vercel AI SDK provides unique advantages when paired with WebScrapingAPI through the Model Context Protocol.

01

TypeScript-first: every MCP tool gets full type inference, IDE autocomplete, and compile-time error checking out of the box

02

Framework-agnostic core works with Next.js, Nuxt, SvelteKit, or any Node.js runtime. same WebScrapingAPI integration everywhere

03

Built-in streaming UI primitives let you display WebScrapingAPI tool results progressively in React, Svelte, or Vue components

04

Edge-compatible: the AI SDK runs on Vercel Edge Functions, Cloudflare Workers, and other edge runtimes for minimal latency

WebScrapingAPI + Vercel AI SDK Use Cases

Practical scenarios where Vercel AI SDK combined with the WebScrapingAPI MCP Server delivers measurable value.

01

AI-powered web apps: build dashboards that query WebScrapingAPI in real-time and stream results to the UI with zero loading states

02

API backends: create serverless endpoints that orchestrate WebScrapingAPI tools and return structured JSON responses to any frontend

03

Chatbots with tool use: embed WebScrapingAPI capabilities into conversational interfaces with streaming responses and tool call visibility

04

Internal tools: build admin panels where team members interact with WebScrapingAPI through natural language queries

WebScrapingAPI MCP Tools for Vercel AI SDK (10)

These 10 tools become available when you connect WebScrapingAPI to Vercel AI SDK via MCP:

01

custom_api_scrape

g. country, session, wait_for). Execute a scrape using advanced custom parameters

02

scrape_and_auto_extract

g. for news or product pages). Scrape with automatic structured data extraction

03

scrape_as_mobile

Scrape as a mobile device using WebScrapingAPI device emulation

04

scrape_ecommerce_product

Returns price, title, and reviews as structured JSON. Scrape product details from Amazon, Walmart, or other supported stores

05

scrape_js_rendered

Slower but captures the full rendered state. Scrape JS-rendered HTML using WebScrapingAPI headless browser

06

scrape_static_html

Pass the full target URL. Scrape raw HTML from any URL using WebScrapingAPI datacenter proxies

07

scrape_via_residential_proxy

Scrape using residential proxies for high anonymity and bypass

08

search_bing_serp

Retrieve structured search engine results from Bing

09

search_google_serp

Provide a query string. Retrieve structured search engine results from Google

10

search_yandex_serp

Retrieve structured search engine results from Yandex

Example Prompts for WebScrapingAPI in Vercel AI SDK

Ready-to-use prompts you can give your Vercel AI SDK agent to start working with WebScrapingAPI immediately.

01

"Scrape the rendered HTML of 'https://example.com/dynamic-dashboard'."

02

"Search Google for 'best wireless noise cancelling headphones' and return structured results."

03

"Get the price and rating for the product at 'https://amazon.com/dp/B09XXX'."

Troubleshooting WebScrapingAPI MCP Server with Vercel AI SDK

Common issues when connecting WebScrapingAPI to Vercel AI SDK through the Vinkius, and how to resolve them.

01

createMCPClient is not a function

Install: npm install @ai-sdk/mcp

WebScrapingAPI + Vercel AI SDK FAQ

Common questions about integrating WebScrapingAPI MCP Server with Vercel AI SDK.

01

How does the Vercel AI SDK connect to MCP servers?

Import createMCPClient from @ai-sdk/mcp and pass the server URL. The SDK discovers all tools and provides typed TypeScript interfaces for each one.
02

Can I use MCP tools in Edge Functions?

Yes. The AI SDK is fully edge-compatible. MCP connections work on Vercel Edge Functions, Cloudflare Workers, and similar runtimes.
03

Does it support streaming tool results?

Yes. The SDK provides streaming primitives like useChat and streamText that handle tool calls and display results progressively in the UI.

Connect WebScrapingAPI to Vercel AI SDK

Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.