# Nationalize MCP for AI Agents AI Agent Connect > Nationalize lets your AI agent predict where a person is likely from based on their name. It uses linguistic data to give you country codes and probability scores for names like 'O'Connor' or 'Silva.' It's perfect for cleaning up user profiles or figuring out where a lead might be located without manual research. ## Overview - **Category:** developer-tools - **Price:** Free - **Endpoint:** https://edge.vinkius.com/vk_preview_KzfhBMZVFCpOsX31Stgg9RxJjW5okZ0uZxpHp1oj/ai-agent-connect - **Tags:** nationality-prediction, demographics, name-analysis, geographic-data, identity-intelligence ## Description You're working through a massive list of names and need to know where these people actually come from. Instead of guessing or digging through separate databases, you can just ask your agent to run them through Nationalize. It looks at naming patterns to give you a ranked list of countries and the likelihood of each. If you're trying to clean up a messy user database or need to group leads by region, this handles the heavy lifting. You can find this and thousands of other connections in the Vinkius catalog, making it easy to add this specific capability to your setup. It's about getting context quickly so you can move on to the actual analysis. You get a clear breakdown of probabilities, which helps you spot trends in your data or just fill in the blanks on a profile. ## Tools ### predict_nationality Give the AI a name and it tells you the most likely country of origin. It's great for quickly identifying regional ties in a dataset. ## 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 ### Get country predictions Predict the most likely country of origin for a name. ### Batch process names Submit up to 10 names at once for faster analysis. ### Score probabilities Receive a ranked list of ISO codes and confidence levels. ### Enrich user profiles Add geographic context to existing identity data. ### Analyze naming trends Identify demographic distributions of names across different cultures. ## Use Cases ### Cleaning a user database A data analyst has a list of 500 names and needs to assign a Region tag to all of them for a marketing campaign. The agent uses predict_nationality to fill these in automatically. ### Lead generation A sales lead comes in with just a name. The agent uses predict_nationality to guess the country so the rep knows which time zone to use for the first call. ### Demographic research A researcher wants to see which countries have the highest frequency of a specific surname across a global dataset to identify migration patterns. ### App feature building A developer wants to add a Where are you from feature to a signup form that populates based on the user's name during the onboarding flow. ## Benefits - Stop guessing origins manually. Use predict_nationality to get instant results for any name. - Batch your work. Submit multiple names at once to save time on large datasets. - Get precise data. Receive ISO country codes and probability scores instead of vague guesses. - Enrich your leads. Add geographic context to user profiles automatically during data ingestion. - Spot trends faster. See the demographic distribution of names across different cultures in seconds. - Save on development. Skip building your own complex linguistic models by using the Nationalize.io API. ## How It Works The bottom line is you get instant geographic context for any name with zero manual research. 1. Connect the Nationalize MCP to your preferred AI client. 2. Provide your Nationalize.io API key if you need higher volume limits. 3. Ask your agent to predict the origin for any name or list of names. ## Frequently Asked Questions **Can Nationalize MCP tell me exactly where someone lives?** No, it predicts the country of origin based on naming patterns. It gives you a probability score, not a specific home address. **Is Nationalize MCP good for large lists of names?** Yes, you can submit multiple names at once. It's built to handle batch requests for data enrichment tasks. **What kind of data does Nationalize MCP provide?** It returns a ranked list of ISO country codes along with a probability score for each country. **Can I use Nationalize MCP for marketing research?** It's perfect for that. You can use it to see the demographic distribution of names across different regions. **Does Nationalize MCP work for all languages?** It analyzes linguistic patterns globally, making it useful for names from many different cultures and regions. **How accurate is the Nationalize MCP prediction?** It provides statistical probabilities based on global data. It's highly effective for best guess scenarios but isn't a replacement for legal documentation. **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.