How to Use the IP2WHOIS MCP in Pydantic AI

Use the IP2WHOIS MCP Server with Pydantic AI for type-safe domain investigations that fail fast on bad data.

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Connect IP2WHOIS MCP to Pydantic AI

Create your Vinkius account to connect IP2WHOIS to Pydantic AI and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup IP2WHOIS with Pydantic AI

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Perplexity

Type-safe domain lookups

Every tool like `lookup_domain_whois` returns data that is strictly validated against your Pydantic models. If the API returns unexpected fields, the request fails instantly, keeping your agent logic clean. This approach prevents silent failures where bad data might otherwise corrupt your agent's state. You define the schema, and the server ensures the response matches it perfectly.

Automated renewal monitoring

Use `check_domain_expiry` to feed expiration dates into your agent's decision logic. Pydantic AI will validate the date format, ensuring your agent acts only on valid, parsed timestamps. Your agent can now trigger alerts for domains nearing their expiration date. It's a reliable way to manage infrastructure without worrying about malformed API responses.

Verify domain availability

Call `check_domain_availability` to confirm if a domain is registered. The tool response is parsed into a boolean or status object, which your Pydantic model enforces at runtime. This gives your agent a clear, type-safe signal for every check it performs. You can build complex workflows knowing that your agent will never process an invalid or empty response.

Setup guide

Set up IP2WHOIS MCP in Pydantic AI

Prerequisites

Python 3.10+ installed
pydantic-ai-slim[fastmcp] package
Active Vinkius subscription with a valid endpoint token

1

Install Pydantic AI with FastMCP
Run pip install "pydantic-ai-slim[fastmcp]". The FastMCP toolset replaces the deprecated MCPServerHTTP class with full protocol support.
2

Configure the FastMCPToolset
Pass a JSON-style config dict to FastMCPToolset with your Vinkius URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports Streamable HTTP, SSE, and Stdio transports.
3

Create and run your agent
Pass the toolset to Agent(toolsets=[toolset]) and call agent.run(). Swap openai:gpt-4o for any supported model — Anthropic, Google, Mistral, or Groq.

agent.py

from pydantic_ai import Agent
from pydantic_ai.toolsets.fastmcp import FastMCPToolset

toolset = FastMCPToolset({
    "mcpServers": {
        "ip2whois-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

agent = Agent(
    "openai:gpt-4o",
    toolsets=[toolset],
    system_prompt="You have access to IP2WHOIS tools.",
)

result = await agent.run("List recent IP2WHOIS transactions")
print(result.output)

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Common questions about IP2WHOIS MCP in Pydantic AI

Yes, you define the expected output schema in Pydantic. The MCP tool output is validated against these models, ensuring only correct data reaches your agent.

The agent throws a validation error immediately. This prevents the agent from hallucinating or using corrupted information during its task.

The server retrieves public WHOIS data. Any registrant info from `get_domain_contacts` is subject to domain-level privacy redactions.

Use the MCPToolset class with your server's HTTP URL. It supports SSE and HTTP, allowing you to plug it directly into your agent definition.

Yes. Pydantic AI is model-agnostic. Whether you use a local LLM or a hosted one, the validation layer remains the same for your IP2WHOIS tools.

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