WebScrapingAPI MCP Server for Vercel AI SDK 10 tools — connect in under 2 minutes
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.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
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();
* 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 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.
Install dependencies
Run npm install @ai-sdk/mcp ai @ai-sdk/openai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the script
Save to agent.ts and run with npx tsx agent.ts
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.
TypeScript-first: every MCP tool gets full type inference, IDE autocomplete, and compile-time error checking out of the box
Framework-agnostic core works with Next.js, Nuxt, SvelteKit, or any Node.js runtime. same WebScrapingAPI integration everywhere
Built-in streaming UI primitives let you display WebScrapingAPI tool results progressively in React, Svelte, or Vue components
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.
AI-powered web apps: build dashboards that query WebScrapingAPI in real-time and stream results to the UI with zero loading states
API backends: create serverless endpoints that orchestrate WebScrapingAPI tools and return structured JSON responses to any frontend
Chatbots with tool use: embed WebScrapingAPI capabilities into conversational interfaces with streaming responses and tool call visibility
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:
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 Vercel AI SDK
Ready-to-use prompts you can give your Vercel AI 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 Vercel AI SDK
Common issues when connecting WebScrapingAPI to Vercel AI SDK through the Vinkius, and how to resolve them.
createMCPClient is not a function
npm install @ai-sdk/mcpWebScrapingAPI + Vercel AI SDK FAQ
Common questions about integrating WebScrapingAPI MCP Server with Vercel AI SDK.
How does the Vercel AI SDK connect to MCP servers?
createMCPClient from @ai-sdk/mcp and pass the server URL. The SDK discovers all tools and provides typed TypeScript interfaces for each one.Can I use MCP tools in Edge Functions?
Does it support streaming tool results?
useChat and streamText that handle tool calls and display results progressively in the UI.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 Vercel AI SDK
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.
