WebScrapingAPI MCP Server for Pydantic AI 10 tools — connect in under 2 minutes
Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect WebScrapingAPI through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
import asyncio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerHTTP
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
server = MCPServerHTTP(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
agent = Agent(
model="openai:gpt-4o",
mcp_servers=[server],
system_prompt=(
"You are an assistant with access to WebScrapingAPI "
"(10 tools)."
),
)
result = await agent.run(
"What tools are available in WebScrapingAPI?"
)
print(result.data)
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.
Pydantic AI validates every WebScrapingAPI tool response against typed schemas, catching data inconsistencies at build time. Connect 10 tools through Vinkius and switch between OpenAI, Anthropic, or Gemini without changing your integration code. full type safety, structured output guarantees, and dependency injection for testable agents.
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 Pydantic AI 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 Pydantic AI via MCP
Follow these steps to integrate the WebScrapingAPI MCP Server with Pydantic AI.
Install Pydantic AI
Run pip install pydantic-ai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the agent
Save to agent.py and run: python agent.py
Explore tools
The agent discovers 10 tools from WebScrapingAPI with type-safe schemas
Why Use Pydantic AI with the WebScrapingAPI MCP Server
Pydantic AI provides unique advantages when paired with WebScrapingAPI through the Model Context Protocol.
Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application
Model-agnostic architecture. switch between OpenAI, Anthropic, or Gemini without changing your WebScrapingAPI integration code
Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors
Dependency injection system cleanly separates your WebScrapingAPI connection logic from agent behavior for testable, maintainable code
WebScrapingAPI + Pydantic AI Use Cases
Practical scenarios where Pydantic AI combined with the WebScrapingAPI MCP Server delivers measurable value.
Type-safe data pipelines: query WebScrapingAPI with guaranteed response schemas, feeding validated data into downstream processing
API orchestration: chain multiple WebScrapingAPI tool calls with Pydantic validation at each step to ensure data integrity end-to-end
Production monitoring: build validated alert agents that query WebScrapingAPI and output structured, schema-compliant notifications
Testing and QA: use Pydantic AI's dependency injection to mock WebScrapingAPI responses and write comprehensive agent tests
WebScrapingAPI MCP Tools for Pydantic AI (10)
These 10 tools become available when you connect WebScrapingAPI to Pydantic AI 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 Pydantic AI
Ready-to-use prompts you can give your Pydantic AI 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 Pydantic AI
Common issues when connecting WebScrapingAPI to Pydantic AI through the Vinkius, and how to resolve them.
MCPServerHTTP not found
pip install --upgrade pydantic-aiWebScrapingAPI + Pydantic AI FAQ
Common questions about integrating WebScrapingAPI MCP Server with Pydantic AI.
How does Pydantic AI discover MCP tools?
MCPServerHTTP instance with the server URL. Pydantic AI connects, discovers all tools, and generates typed Python interfaces automatically.Does Pydantic AI validate MCP tool responses?
Can I switch LLM providers without changing MCP code?
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 Pydantic AI
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.