Can I scrape a URL directly without creating a scraper first?

Yes! Use the `direct_scrape` tool and provide the URL. It will use Browserhub's real browsers to render the page and extract data based on your parameters instantly.

How do I monitor the progress of a scraping job?

Simply ask the agent to `get_scraping_job` and provide the Job ID. It will return the current status (e.g., pending, running, finished) and the result data once ready.

Can I specify a proxy location for my scraping request?

Yes. When using `direct_scrape`, you can provide a `proxy_country` code. Use the `list_proxy_locations` tool to see the full list of supported countries in your account.

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

Name: Browserhub
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 Browserhub 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

Open in ChatGPT Open in Claude Open in Perplexity

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 Browserhub "
            "(10 tools)."
        ),
    )

    result = await agent.run(
        "What tools are available in Browserhub?"
    )
    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 Browserhub MCP Server

Connect your Browserhub.io account to any AI agent and orchestrate your web scraping, data extraction, and proxy management workflows through natural conversation.

Pydantic AI validates every Browserhub 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

Scraper Oversight — List all your configured scrapers and blueprints, and retrieve detailed metadata for each.
Job Execution — Trigger scraping jobs with dynamic URL overrides and monitor their progress in real-time.
Direct Scraping — Perform one-off URL extractions using real browsers without pre-defined scrapers.
Data Retrieval — Retrieve structured data captured by your jobs directly into your workspace.
Infrastructure Management — List available proxy locations and check your account credit balance.
Task History — List and inspect all your previous scraping jobs.

The Browserhub 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 Browserhub to Pydantic AI via MCP

Follow these steps to integrate the Browserhub 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 Browserhub with type-safe schemas

Why Use Pydantic AI with the Browserhub MCP Server

Pydantic AI provides unique advantages when paired with Browserhub 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 Browserhub integration code

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

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

Browserhub + Pydantic AI Use Cases

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

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

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

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

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

Browserhub MCP Tools for Pydantic AI (10)

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

direct_scrape

Perform a one-off URL scrape without a pre-defined scraper

get_account_balance

Check account credit balance

get_blueprint

Get details of a specific blueprint

get_scraper

Get details of a specific scraper

get_scraping_job

Get status and results of a scraping job

list_blueprints

List all scraper blueprints

list_proxy_locations

List all available proxy locations

list_scrapers

List all configured scrapers

list_scraping_jobs

List all scraping jobs

run_scraper

Start a scraping job using a specific scraper

Example Prompts for Browserhub in Pydantic AI

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

"List all my configured scrapers in Browserhub."

"Scrape the URL https://example.com using the 'E-commerce' scraper."

"Check my Browserhub account credit balance."

Troubleshooting Browserhub MCP Server with Pydantic AI

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

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Browserhub + Pydantic AI FAQ

Common questions about integrating Browserhub 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 Browserhub MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.