How to Use the NS1 (IBM NS1 Premium DNS API) MCP in Pydantic AI

Q: Can I list data sources safely?

Use listdatasources and rely on the model validation to filter the results. Your agent will only process the data that matches your schema.

Use Pydantic AI for type-safe interaction with the NS1 (IBM NS1 Premium DNS API) MCP Server.

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Connect NS1 (IBM NS1 Premium DNS API) MCP to Pydantic AI

Create your Vinkius account to connect NS1 (IBM NS1 Premium DNS API) 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 NS1 (IBM NS1 Premium DNS API) with Pydantic AI

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Validated DNS operations in Pydantic AI

Every response from the server is checked against Pydantic models. If `get_zone` returns malformed data, your agent stops immediately. This protects your DNS configuration from corrupted API payloads. You get strict runtime validation for every record update you perform.

Reliable record management for Pydantic AI

You perform precise updates using `create_record` and `delete_record`. The agent validates the schema of every request before it hits the API. This eliminates silent failures. If your logic produces an invalid record type, Pydantic AI catches it before the request is even sent.

Orchestrate zones with Pydantic AI

Manage your entire DNS topology using `list_zones` and `update_zone`. The agent maps the API output to your defined models for perfect state alignment. This ensures your agent knows the exact state of your zones at all times. It removes ambiguity from your automated infrastructure pipelines.

Setup guide

Set up NS1 (IBM NS1 Premium DNS API) 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": {
        "ns1-ibm-ns1-premium-dns-api-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

agent = Agent(
    "openai:gpt-4o",
    toolsets=[toolset],
    system_prompt="You have access to NS1 (IBM NS1 Premium DNS API) tools.",
)

result = await agent.run("List recent NS1 (IBM NS1 Premium DNS API) transactions")
print(result.output)

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Common questions about NS1 (IBM NS1 Premium DNS API) MCP in Pydantic AI

It provides type-safe validation for every API call. This prevents hallucinated fields from breaking your DNS records.

Yes. The server provides structured data that the agent validates against your models at runtime.

The agent treats validation errors as first-class exceptions. You handle these in your main agent loop to ensure system stability.

Use `list_data_sources` and rely on the model validation to filter the results. Your agent will only process the data that matches your schema.

The server operates within a secure, ephemeral boundary. Your DNS records are never stored beyond the immediate processing of your agent's request.

Use it with your favorite AI tools

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