# Nationalize MCP

> Nationalize uses name analysis to predict a person's most likely country of origin. It processes names or last names and returns a ranked list of ISO country codes along with precise probability scores. This tool lets your AI client instantly enrich data fields, allowing developers and analysts to classify leads or user profiles by probable geographic context.

## Overview
- **Category:** developer-tools
- **Price:** Free
- **Tags:** nationality-prediction, demographics, name-analysis, geographic-data, identity-intelligence

## Description

You're running into data fields that just need a geographic context, and you don't want to manually research every lead. That's where the `predict_nationality` tool comes in. It predicts a person's most likely country of origin based on their name. The best results come when you feed it last names.

When your AI client calls this function, it processes the input against its massive demographic database and immediately sends back a ranked list. This list includes ISO country codes and precise probability scores for each potential match. You get to see exactly how confident the model is about every single suggestion. It’s not just guessing; you're getting statistical weights.

Need to predict origin from a handful of names? Submit one or more full names, and the tool provides immediate predictions about their country of origin. The output isn't just a list—it's structured data that tells you which countries are most likely, ranked by probability. You can use this mechanism right within your workflow.

If you’re dealing with big datasets, forget running one call per record. This tool lets you analyze name batches; you can process up to ten names in a single request. That rapid classification ability saves serious time when you're sorting through thousands of user profiles or CRM entries that need geographic tagging.

This predictive function is perfect for enriching lead data. You can take raw user profiles and instantly append probable geographic context derived directly from the name field. Your agent updates your database records by adding reliable, calculated country information. This means you don't just have names; you've got classified leads with immediate actionable intelligence.

The model doesn't just tell you a country; it gives you the probability score for that match. If one country has a 92% chance and another has a 68% chance, you know exactly which lead to focus on first. This scoring system is key because it lets you filter out low-confidence suggestions. You don't waste time following up on guesses.

Think about your data pipeline: when names flow into the system, you can run `predict_nationality` as a mandatory pre-processing step. Instead of having to write complex, fragile regex rules or use country code lookups that only work for initials, you just pass the name through and let the tool do the heavy lifting. It handles the global linguistic patterns so you don't have to worry about them.

It’s a direct way to classify people by probable geographic context. Whether it's identifying leads in a sales pipeline or classifying user profiles for marketing segmentation, this tool gives your agent the precise data points needed right out of the gate. You get ISO country codes, which is exactly what most other systems require—no conversion steps necessary.

You run the `predict_nationality` function with names like 'Smith' or 'Chen,' and you instantly receive a machine-readable output showing the top three countries and their associated probabilities. It’s fast. It's reliable. You just connect your AI client, invoke the tool, and get accurate demographic data back to use in your application logic.

## Tools

### predict_nationality
Predicts a person's most likely country of origin and provides probability scores based on their name, with the best results coming from last names.

## Prompt Examples

**Prompt:** 
```
Predict the nationality for the name 'Dmitry'.
```

**Response:** 
```
I've analyzed the name 'Dmitry'. The most likely country of origin is Russia (RU) with a probability of 0.15, followed by Ukraine (UA) and Belarus (BY).
```

**Prompt:** 
```
What are the most likely countries of origin for 'Silva' and 'Tanaka'?
```

**Response:** 
```
For 'Silva', the top prediction is Brazil (BR) with high confidence. For 'Tanaka', the most likely origin is Japan (JP). Would you like the full probability breakdown for both?
```

**Prompt:** 
```
Check the origin of the last name 'O'Connor'.
```

**Response:** 
```
The name 'O'Connor' shows a very strong correlation with Ireland (IE) at 0.92 probability. Other minor matches include the United Kingdom and Australia.
```

## Capabilities

### Predict Origin from Name
Submit one or more names to receive statistical predictions about their potential country of origin.

### Enrich Lead Data
Update user profiles or CRM entries by appending probable geographic context derived directly from a person's name.

### Analyze Name Batches
Process up to ten names in one call, allowing for rapid demographic classification across large datasets.

## Use Cases

### Onboarding a New Customer List
Your CRM exports a list of 500 new contacts, but they only have names. Your agent runs `predict_nationality` on the entire batch. The output is structured data, allowing you to automatically tag and segment every lead by their predicted country code before passing it to the sales team.

### Analyzing Academic Data Sets
A research project requires knowing the origin of historical figures listed only by name. Your agent feeds these names into `predict_nationality`. The tool returns a ranked list of potential countries, helping you map demographic distribution across cultures.

### Building Identity Verification Services
You're building an application that needs to validate user identity. Instead of complex checks, your agent uses `predict_nationality` on the provided last name. It returns a strong correlation score (e.g., 0.92), giving you high-confidence data for immediate use.

### Data Cleaning and Validation
You receive messy spreadsheet data where country fields are often blank or wrong. Your agent runs `predict_nationality` on the names in the 'Full Name' column. The tool fills in the missing geographic context, cleaning up your dataset with minimal human effort.

## Benefits

- Instantly enrich user profiles. Instead of having a blank 'Country' field, you get probable geographic context by running the `predict_nationality` tool on names.
- Process data in batches. You can submit up to ten names at once. This lets your agent classify large lists of leads or research entries quickly, saving manual lookups.
- Get statistical confidence scores. The output includes probability percentages (e.g., 0.92 for Ireland). This tells you how certain the prediction is, letting you filter out weak matches.
- Use it on last names. The tool notes that sending a person's last name provides the most accurate and reliable results, improving your data quality immediately.
- Target specific regions. You can build filters or queries around the ISO country codes returned by `predict_nationality`, letting you focus only on leads from high-value markets.

## How It Works

The bottom line is: give it names, get back probabilities for where they probably come from.

1. Your AI client calls the `predict_nationality` tool and provides the name (or list of names) you want analyzed.
2. The Nationalize server processes this input, cross-referencing linguistic patterns against global demographic data.
3. You receive a structured output listing potential country codes, their ranking order, and associated probability scores.

## Frequently Asked Questions

**How do I use Nationalize to predict nationality?**
You call the `predict_nationality` tool with the name(s) you want analyzed. The agent handles the rest, returning a ranked list of potential countries and their probabilities.

**Is predicting nationality reliable using Nationalize?**
The results are statistical predictions based on global data patterns. Always check the probability score; a high score (like 0.92) indicates very strong correlation, while lower scores suggest ambiguity.

**What is the best way to run Nationalize?**
The tool documentation notes that passing the last name provides the most accurate results for `predict_nationality`. Try to structure your input around the surname first.

**Can I predict nationality for multiple names with Nationalize?**
Yes. The `predict_nationality` tool allows you to submit up to ten names in a single call, making batch processing efficient and scalable.

**What do I need to authenticate when using the `predict_nationality` tool in Nationalize?**
An API key is required for high-volume usage. You enter your specific Nationalize API Key directly into the server configuration. This ensures your AI client tracks usage accurately and prevents rate limit issues.

**Does the `predict_nationality` tool work best with full names or specific parts of the name using Nationalize?**
The tool performs best when you provide only the last name. Sending just the surname gives the prediction engine the most accurate data to analyze for origin.

**Are there rate limits when running high-volume name analysis using the Nationalize MCP Server?**
Yes, usage is governed by API rate limits. If you send too many requests in a short time, your client will receive an error code. Implement a delay or use batch processing to stay within the established quota.

**What format does the `predict_nationality` tool provide for name analysis results from Nationalize?**
The output is structured data, providing a ranked list of ISO country codes. Each prediction includes both the country code and an explicit probability score showing its confidence level.

**How many names can I analyze in a single request?**
You can pass a list of up to 10 names to the `predict_nationality` tool per request. This allows for efficient batch processing of datasets.

**What kind of results does the tool return?**
The tool returns a ranked list of ISO 3166-1 alpha-2 country codes (like 'US', 'BR', 'JP') along with a probability score for each, indicating the likelihood of that origin.

**Is an API key required to use this server?**
The `NATIONALIZE_API_KEY` is optional. You can perform basic testing without it, but for higher volume or production use, providing a key is recommended to avoid rate limits.