Are the exported results structured JSON or raw HTML?

The API returns highly structured, pre-parsed JSON. For example, a Google Search request directly returns organized arrays of organic results, related queries, ads, and knowledge panels — there's no need to write code to parse the HTML DOM.

Do I need to manage my own residential proxies?

No. Oxylabs handles all infrastructure on the backend, automatically rotating residential proxies, fingerprinting, and bypassing CAPTCHAs. You just provide the search query.

Can I search Google News for PR tracking?

Yes, the google_news_search tool natively queries the News tab, returning structured articles with publishers, titles, snippets, and exact publication timestamps, making it highly effective for PR and brand tracking.

Oxylabs SERP MCP Server for Pydantic AI 10 tools — connect in under 2 minutes

Name: Oxylabs SERP
Availability: InStock
Author: Vinkius

ai.pydantic.dev/mcp

Built by Vinkius GDPR 10 Tools SDK

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Oxylabs SERP through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

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Vinkius supports streamable HTTP and SSE.

python

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 Oxylabs SERP "
            "(10 tools)."
        ),
    )

    result = await agent.run(
        "What tools are available in Oxylabs SERP?"
    )
    print(result.data)

asyncio.run(main())

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* 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 Oxylabs SERP MCP Server

Bring the Oxylabs SERP Scraper API directly into your AI workflows. Perform high-volume, structured data extraction across all major search engines without worrying about proxy rotation, CAPTCHAs, or HTML parsing.

Pydantic AI validates every Oxylabs SERP 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

Google Ecosystem — Extract parsed data from Google Search (organic, snippets), Google Images, Google News, Google Shopping, Google Scholar, and Google Travel/Hotels
Bing Search — Extract organic search rankings and rich snippets from Microsoft Bing
Yandex Search — Scrape the leading Russian search engine for regional SEO analysis
Baidu Search — Extract search engine results pages from China's leading search provider
YouTube Search — Parse video rankings, channel details, and views from YouTube search results

The Oxylabs SERP 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 Oxylabs SERP to Pydantic AI via MCP

Follow these steps to integrate the Oxylabs SERP 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 Oxylabs SERP with type-safe schemas

Why Use Pydantic AI with the Oxylabs SERP MCP Server

Pydantic AI provides unique advantages when paired with Oxylabs SERP 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 Oxylabs SERP integration code

Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors

Dependency injection system cleanly separates your Oxylabs SERP connection logic from agent behavior for testable, maintainable code

Oxylabs SERP + Pydantic AI Use Cases

Practical scenarios where Pydantic AI combined with the Oxylabs SERP MCP Server delivers measurable value.

Type-safe data pipelines: query Oxylabs SERP with guaranteed response schemas, feeding validated data into downstream processing

API orchestration: chain multiple Oxylabs SERP tool calls with Pydantic validation at each step to ensure data integrity end-to-end

Production monitoring: build validated alert agents that query Oxylabs SERP and output structured, schema-compliant notifications

Testing and QA: use Pydantic AI's dependency injection to mock Oxylabs SERP responses and write comprehensive agent tests

Oxylabs SERP MCP Tools for Pydantic AI (10)

These 10 tools become available when you connect Oxylabs SERP to Pydantic AI via MCP:

baidu_search

Inspect deep internal arrays mitigating specific Plan Math

bing_search

Dispatch an automated validation check routing explicit Gateway history

google_images_search

Perform structural extraction of properties driving active Account logic

google_news_search

Provision a highly-available JSON Payload generating hard Customer bindings

google_scholar_search

Irreversibly vaporize explicit validations extracting rich Churn flags

google_search

Identify bounded CRM records inside the Headless Oxylabs SERP Platform

google_shopping_search

Retrieve explicit Cloud logging tracing explicit Vault limits

google_travel_search

Enumerate explicitly attached structured rules exporting active Billing

yandex_search

Identify precise active arrays spanning native Gateway auth

youtube_search

Identify precise active arrays spanning native Hold parsing

Example Prompts for Oxylabs SERP in Pydantic AI

Ready-to-use prompts you can give your Pydantic AI agent to start working with Oxylabs SERP immediately.

"Search Google for 'best enterprise LLMs' and summarize the top organic results."

"Check Google Travel for hotels in Tokyo next weekend."

"Search YouTube for 'Next.js 15 tutorials'."

Troubleshooting Oxylabs SERP MCP Server with Pydantic AI

Common issues when connecting Oxylabs SERP to Pydantic AI through the Vinkius, and how to resolve them.

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Oxylabs SERP + Pydantic AI FAQ

Common questions about integrating Oxylabs SERP MCP Server with Pydantic AI.

How does Pydantic AI discover MCP tools?

Create an 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?

Yes. When you define result types as Pydantic models, every tool response is validated against the schema. Invalid data raises a clear error instead of silently corrupting your pipeline.

Can I switch LLM providers without changing MCP code?

Absolutely. Pydantic AI abstracts the model layer. your Oxylabs SERP MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.