Public Suffix Extractor MCP Server for Pydantic AIGive Pydantic AI instant access to 1 tools to Extract Domain

Name: Public Suffix Extractor
Price: 29 USD
Availability: InStock
Rating: 5.0 (1 reviews)
Author: Vinkius

GDPR Free for Subscribers

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

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The Public Suffix Extractor MCP Server for Pydantic AI is a standout in the Developer Tools category — giving your AI agent 1 tools to work with, ready to go from day one.

Built for AI Agents by Vinkius

Vinkius delivers Streamable HTTP and SSE to any MCP client

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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 Public Suffix Extractor "
            "(1 tools)."
        ),
    )

    result = await agent.run(
        "What tools are available in Public Suffix Extractor?"
    )
    print(result.data)

asyncio.run(main())

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About Public Suffix Extractor MCP Server

When an analytics agent processes URLs, it cannot guess that in app.vinkius.co.uk the TLD is .co.uk (not .uk). This MCP uses the official Mozilla Public Suffix List to fragment hostnames with 100% accuracy.

Pydantic AI validates every Public Suffix Extractor tool response against typed schemas, catching data inconsistencies at build time. Connect 1 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.

The Superpowers

Official List: Uses the same Public Suffix List maintained by Mozilla and used by every major browser.
Complex TLDs: Correctly handles .co.uk, .com.br, .org.au, .amazonaws.com, and 9,000+ other suffixes.

The Public Suffix Extractor MCP Server exposes 1 tools through the Vinkius. Connect it to Pydantic AI in under two minutes — credentials fully managed, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

All 1 Public Suffix Extractor tools available for Pydantic AI

When Pydantic AI connects to Public Suffix Extractor through Vinkius, your AI agent gets direct access to every tool listed below — spanning url-parsing, tld-extraction, domain-analysis, and more. Every call runs in a secure, isolated environment with full audit visibility. Beyond a simple connection, you get real-time monitoring of agent activity, enterprise governance, and optimized token usage.

extract

Extract domain on Public Suffix Extractor

The AI cannot reliably determine that the TLD of "app.vinkius.co.uk" is ".co.uk" (not ".uk"). This engine uses the official Mozilla Public Suffix List to fragment hostnames with 100% accuracy. Extracts the true root domain, TLD, subdomain, and SLD from any hostname using the official Mozilla Public Suffix List. Handles complex TLDs like .co.uk, .com.br correctly

Connect Public Suffix Extractor to Pydantic AI via MCP

Follow these steps to wire Public Suffix Extractor into Pydantic AI. The entire setup takes under two minutes — your credentials stay safe behind Vinkius.

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 1 tools from Public Suffix Extractor with type-safe schemas

Why Use Pydantic AI with the Public Suffix Extractor MCP Server

Pydantic AI provides unique advantages when paired with Public Suffix Extractor 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 Public Suffix Extractor integration code

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

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

Public Suffix Extractor + Pydantic AI Use Cases

Practical scenarios where Pydantic AI combined with the Public Suffix Extractor MCP Server delivers measurable value.

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

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

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

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

Example Prompts for Public Suffix Extractor in Pydantic AI

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

"What is the root domain of app.vinkius.co.uk?"

"Extract the registrable domain from https://shop.example.com.br/products?id=1"

"Is mybucket.s3.amazonaws.com a registrable domain or a cloud subdomain?"

Troubleshooting Public Suffix Extractor MCP Server with Pydantic AI

Common issues when connecting Public Suffix Extractor to Pydantic AI through Vinkius, and how to resolve them.

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Public Suffix Extractor + Pydantic AI FAQ

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

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