# Genderize MCP > Genderize MCP predicts a person's likely gender based on their first name using global statistical data. This tool provides probability scores and localizes results by country, helping you quickly enrich lead lists or profile data. It handles single names, bulk batches of up to 10 names, and supports specific regional checks for countries like the US, UK, and Brazil. ## Overview - **Category:** developer-tools - **Price:** Free - **Tags:** gender-prediction, data-enrichment, statistical-analysis, name-processing, api-integration ## Description You've got a list of leads, but your CRM is missing gender markers. This MCP connects directly to a massive database containing over 114 million name records, letting you estimate gender probabilities right from your chat interface. It’s not just guessing; it provides statistical certainty scores (0.0 to 1.0) and tells you how many records informed the prediction. You can even specify a country using ISO codes—this massively improves accuracy for regional naming patterns. Using this MCP through Vinkius means you don't have to leave your AI client or mess with an API key flow; you just ask, and it handles the data crunching. Need to run predictions on hundreds of names? Use the bulk function. It makes cleaning up large datasets simple, turning a manual spreadsheet task into a quick conversation. ## Tools ### verify_api_connection Runs a check to confirm the MCP's connection status with the underlying data source. ### estimate_gender_brazil Specifically predicts the gender probability for names originating in Brazil. ### estimate_gender_spain Predicts the gender probability of a single first name using data specific to Spain. ### estimate_gender_france Predicts the gender probability for names localized to France. ### estimate_gender_uk Determines gender probabilities for names associated with the UK region. ### estimate_gender Predicts the gender probability of a single first name using global data. ### estimate_gender_us Predicts the gender probability of a single first name using US-specific data patterns. ### estimate_genders_bulk Processes and predicts genders for multiple names in one batch request. ## Prompt Examples **Prompt:** ``` Estimate the gender for the name 'Peter'. ``` **Response:** ``` Predicting gender... For the name 'Peter', Genderize.io estimates a 'male' identity with 99% probability based on 165,452 records. ``` **Prompt:** ``` Predict the genders for these names: ['Alice', 'Bob', 'Charlie']. ``` **Response:** ``` Processing names... I've retrieved estimations for all 3 names: Alice (female, 98%), Bob (male, 99%), and Charlie (male, 56%). ``` **Prompt:** ``` What is the predicted gender for 'Sasha' in Russia (RU)? ``` **Response:** ``` Checking local patterns... In Russia (RU), the name 'Sasha' is estimated as 'male' with 64% probability. ``` ## Capabilities ### Estimate single name gender Get an immediate probability assessment for one first name. ### Process large batches of names Send up to 10 names at once and get all the gender predictions back in a single request. ### Localize prediction by country Adjust name probability checks using specific ISO codes (e.g., US or FR) for accurate regional results. ### Validate API connection status Check if the MCP can successfully connect and communicate with the underlying data source. ## Use Cases ### Cleaning up a global CRM export A Marketing Ops engineer gets a list of 50 names from Brazil and the US. Instead of running two separate scripts, they prompt their agent: 'Predict gender for this batch of names using Brazilian and US data.' The agent uses `estimate_genders_bulk` combined with specialized tools like `estimate_gender_brazil` to return a complete, localized profile. ### Validating user signup forms A developer needs to build a conditional logic gate in their application. They prompt: 'Verify the name Sasha for Russia.' The agent uses `estimate_gender_us` (or another regional tool) to get an immediate, statistically backed answer, preventing bad data from entering the system. ### Analyzing target demographics A Growth Manager wants to know if a specific name is more likely male or female in the UK. They ask: 'What's the predicted gender for Emily in the UK?' The agent calls `estimate_gender_uk` and returns the probability, allowing them to adjust campaign targeting immediately. ### Testing data pipeline reliability A Data Analyst needs to ensure their entire naming pipeline is ready before a big launch. They run `verify_api_connection` first, confirming that the MCP can talk to the source database, eliminating integration risk. ## Benefits - Stop guessing gender. Use `estimate_gender` to get statistical certainty scores (0.0 to 1.0) for any name instantly. - Process entire lead lists fast. The `estimate_genders_bulk` tool handles up to 10 names in one go, saving huge amounts of time on data enrichment. - Get regional accuracy. Instead of general predictions, use specialized tools like `estimate_gender_us` or `estimate_gender_brazil` for perfect localization. - Maintain connection integrity. Run `verify_api_connection` to make sure your MCP is online and ready before a critical batch job runs. - It works through natural chat. You never need to worry about API calls or complex syntax; just talk to your agent. ## How It Works The bottom line is, you talk to your agent like normal and it handles the database lookups automatically. 1. Connect this MCP through Vinkius to your preferred AI client. 2. Optionally, enter your API key into the settings for higher rate limits. 3. Ask your agent a direct question, like 'What is the predicted gender for John in the US?' ## Frequently Asked Questions **Is an API Key required for Genderize.io?** No, you can use the service for free without an API key for up to 100 requests per day. For higher volume, you can obtain a key from genderize.io. **How accurate is the gender prediction?** The API returns a 'probability' score between 0.0 and 1.0. A score of 0.99 means the API is 99% certain of the associated gender based on its database. **Can I localise the results for a specific country?** Yes! Use the 'countryId' parameter with an ISO 3166-1 alpha-2 code (e.g., 'BR' for Brazil) to get results optimized for that specific region. **How many names can I check at once?** The 'estimate_genders_bulk' tool allows you to check up to 10 names in a single API request, which is efficient for processing small lists. **What steps should I take if I'm troubleshooting my setup using the `verify_api_connection` tool?** The `verify_api_connection` tool checks your API credentials and general service connectivity. If it fails, double-check that you entered a valid key in the Vinkius Marketplace settings or that your rate limit hasn't been exceeded. **If I need to process more than 10 names at once, how should I handle high volume requests with `estimate_genders_bulk`?** You must use a paid API key for bulk processing. Once you upgrade your account and provide the key, the rate limits increase significantly, allowing you to send large lists of names efficiently. **When I run `estimate_gender`, what specific data points does my AI agent get back?** Your agent receives the predicted gender (male/female), the statistical probability score (0.0 to 1.0), and the total record count used for that calculation. This gives you clear context on the prediction's reliability. **Do I have to use dedicated tools like `estimate_gender_brazil` instead of the main tool when checking regional names?** It’s best practice to use the specialized country tools for maximum accuracy. These specific endpoints are built with local naming conventions, giving you better results than relying solely on the general name estimator.