How to Use the Nationalize MCP in OpenAI Agents SDK

Q: How do I set up Nationalize with OpenAI Agents SDK?

Install the package using pip install openai-agents and define the server with MCPServerStreamableHttp. Pass this instance inside the mcpservers list when initializing your agent. The framework handles the rest of the connection details.

Q: What is the most accurate way to query Nationalize in OpenAI Agents SDK?

Send the last name instead of the full name to the predictnationality tool. Surnames have much stronger geographical correlation in the underlying dataset. This practice reduces noise and returns higher confidence scores.

Q: Can I trace Nationalize API calls inside OpenAI Agents SDK?

Yes, every call to the predictnationality tool appears in your OpenAI developer dashboard. You get full execution traces, latency metrics, and payload logs for each request. This transparency simplifies debugging in live environments.

Get instant name-to-nationality predictions in your OpenAI Agents SDK production pipelines without manual API routing.

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Connect Nationalize MCP to OpenAI Agents SDK

Create your Vinkius account to connect Nationalize to OpenAI Agents SDK 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 Nationalize with OpenAI Agents SDK

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Predict demographic origins via `predict_nationality`

The `predict_nationality` tool on this MCP Server queries the Nationalize.io API to estimate geographic origin probabilities from a surname string. Your agent passes the target name directly to the Vinkius-hosted endpoint, bypassing custom HTTP client setups. Surnames yield the most accurate results for this lookup. The system returns structured country codes and confidence scores, letting your agent run downstream logic based on geographical probability.

Secure OpenAI Agents SDK tool execution

This MCP Server integrates with the OpenAI Agents SDK to expose the nationality tool automatically. You initialize `MCPServerStreamableHttp` within an async context manager and pass it to the agent constructor. Built-in guardrails validate agent actions before hitting the external endpoint. You track every single API request and response on the OpenAI developer dashboard, keeping full visibility over your production pipelines.

Fast tool discovery and runtime caching

The MCP client discovers the `predict_nationality` tool with zero manual configuration. By setting `cacheToolsList=True`, you avoid redundant schema lookups on every single agent run. This configuration keeps latency low when processing batch lists. Your agent quickly maps names to regions, handing off tasks to specialized regional sub-agents based on the resulting country codes.

Setup guide

Set up Nationalize MCP in OpenAI Agents SDK

Prerequisites

Python 3.10+ installed
openai-agents package (pip install openai-agents)
Active Vinkius subscription with a valid endpoint token

1

Install the SDK

Run pip install openai-agents to install the OpenAI Agents SDK. The MCP integration is built-in — no extra dependencies needed.
2

Connect via SSE transport

Use MCPServerSse with your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. The SDK auto-discovers all Nationalize tools at runtime.
3

Create your Agent

Pass the MCP to Agent(mcp_servers=[server]). The agent receives Nationalize tools as native definitions — JSON schemas resolve automatically.
4

Run the agent

Call Runner.run(agent, prompt) to execute. The agent invokes the appropriate Nationalize tools and returns structured results. Copy the full example on the right to get started.

agent.py

import asyncio
from agents import Agent, Runner
from agents.mcp import MCPServerSse

async def main():
    async with MCPServerSse(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ) as server:
        agent = Agent(
            name="Nationalize Agent",
            instructions="You have access to Nationalize tools.",
            mcp_servers=[server],
        )
        result = await Runner.run(agent, "List recent transactions")
        print(result.final_output)

asyncio.run(main())

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Common questions about Nationalize MCP in OpenAI Agents SDK

Install the package using `pip install openai-agents` and define the server with `MCPServerStreamableHttp`. Pass this instance inside the `mcp_servers` list when initializing your agent. The framework handles the rest of the connection details.

Send the last name instead of the full name to the `predict_nationality` tool. Surnames have much stronger geographical correlation in the underlying dataset. This practice reduces noise and returns higher confidence scores.

Yes, every call to the `predict_nationality` tool appears in your OpenAI developer dashboard. You get full execution traces, latency metrics, and payload logs for each request. This transparency simplifies debugging in live environments.

Vinkius manages the underlying connection pool to the Nationalize API. Your agent only communicates with the secure V8 sandbox, which buffers requests to prevent rate-limit failures. This MCP Server architecture keeps your production runs stable.

The server processes only the name strings you explicitly pass to the `predict_nationality` tool. Vinkius runs the server in an ephemeral sandbox, meaning no personal data or name records are written to persistent storage.

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