IBGE Nomes MCP for AI. Track Brazilian Name Popularity by Decade
Works with every AI agent you already use
…and any MCP-compatible client








Connect to your AI in seconds.
IBGE Nomes provides direct access to Brazil's official naming statistics from IBGE. It lets you analyze how popular names were across different decades, genders, or even specific regions.
Quickly check birth frequency for names like 'Maria' or rank the top 10 most common names in a given state and time period.
What your AI can do
Get name frequency
Determines the number of births per decade for one or more specified names using a pipe separator (|).
Get names ranking
Provides a ranked list of the most frequent names based on specific filters like gender and time period.
Find the number of times specific names were registered across different decades in Brazilian history.
Get a ranked list of the most common names, applying filters for gender and time period.
Simultaneously check the historical frequency of several different names to spot comparative trends.
Limit name statistics to specific Brazilian states or municipalities for regional analysis.
Ask an AI about this
Waiting for input…
IBGE Nomes: 2 Tools for Demographics
Use these specialized tools to run targeted queries on Brazilian naming history, generating both frequency reports and ranked lists.
Make your AI actually useful.
Add this MCP to Claude, Cursor, or Windsurf and your AI stops guessing. It gets real tools to look things up, take action, and handle the stuff you keep doing by hand.
Start using IBGE Nomes on VinkiusGet Name Frequency
Determines the number of births per decade for one or more specified names using a pipe separator (|).
Get Names Ranking
Provides a ranked list of the most frequent names based on specific filters like...
Security and governance baked right in.
Pick your AI client below to get set up. Just create a Vinkius account, subscribe, and you're instantly up and running. We handle the entire backend infrastructure, delivering out-of-the-box support for HTTPS Streamable, SSE, and OAuth2—zero messy routing required.
Choose How to Get Started
Build a custom MCP for your own tools, or connect a ready-made integration from our catalog.
Build Your Own
Turn any API into an MCP. Import a spec, define Agent Skills, or deploy with MCPFusion.
- Import from OpenAPI, Swagger, or YAML specs
- Create Agent Skills with progressive disclosure
- Deploy to edge with MCPFusion framework
- Built in DLP, auth, and compliance on every call
- Real time usage dashboard and cost metering
- Publish to catalog or keep private
Make Your AI Do More
Start with IBGE Nomes, then connect any of our 5,100+ other servers whenever your AI needs more. One click, no limits.
- Use this MCP plus 5,100+ others, all in one place
- Add new capabilities to your AI anytime you want
- Every connection is secured and compliant automatically
- Track usage and costs across all your servers
- Works with Claude, ChatGPT, Cursor, and more
- New servers added to the catalog every week
Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by IBGE. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.
VINKIUS INFRASTRUCTURE
Cloud Hosted
Managed infra
V8 Isolated
Sandboxed per request
Zero-Trust Proxy
No stored credentials
DLP Enforced
Policy on every call
GDPR Compliant
EU data residency
Token Compression
~60% cost reduction
Works with Claude, ChatGPT, Cursor, and more
The Model Context Protocol standardizes how applications expose capabilities to LLMs. Instead of operating in isolation, your AI gains direct access to external platforms, live data, and real-world actions through secure, standardized connections.
This connection provides 2 powerful capabilities that interface natively with Claude, ChatGPT, Cursor, and other compatible AI platforms. No middleware. No custom integration required.
Tracking name popularity used to feel like deep academic digging.
Before this connector, figuring out Brazilian name trends meant consulting dense, PDF-based government reports. You'd spend hours manually searching tables for a specific decade or state ID. Then you’d have to copy and paste the numbers into a spreadsheet, trying to plot the curve yourself.
Now, your agent handles that entire process. Instead of manual data extraction, you just ask: 'Show me the trend for X.' The MCP fetches the precise statistics from IBGE and gives you the analysis instantly in plain text.
Get Name Frequency Data with `get_name_frequency`
You no longer need to cross-reference multiple annual reports. The tool takes a list of names, like 'MARIA|ENZO', and provides their birth counts across the chosen decades in one single query.
This means you stop managing data sources and start focusing on insights. You get the answer immediately.
What your AI can actually do with this
Need to track name trends in Brazil? This MCP connects your AI agent directly to the IBGE census data. You can look up how often any specific name was born over multiple decades, giving you deep insight into cultural shifts. Beyond simple frequency checks, you can generate official rankings of the most popular names, filtering by gender or state ID.
This makes it perfect for historical research or fiction writing that demands accuracy. By connecting this data source through your Vinkius subscription, your AI client treats Brazil’s naming history like a simple lookup table, allowing complex demographic questions to resolve into concrete statistics.
019e38ab-d6a3-7300-94e5-439cebd9df57 Here's how it actually works
The bottom line is that you ask a question about Brazilian names, and this MCP pulls the verified statistics from IBGE instantly.
Subscribe to this MCP in Vinkius. You don't need an API key because it uses the public IBGE Open Data API.
Direct your AI agent (Claude, Cursor, etc.) to perform a specific query, like 'Compare the frequency of name X and Y in the 1980s.'
The MCP retrieves the official data points for you and presents them directly back to your chat window.
Who is this actually for?
This MCP serves sociologists who need hard data on demographic change. It's also crucial for content creators building historical fiction or writers needing highly accurate naming conventions. If your work depends on knowing how culture reflects in names, this is what you need.
Analyzing demographic shifts by tracking name frequency patterns across different Brazilian regions and decades.
Validating fictional settings or literary characters by checking the most popular names in a specific decade and state.
Building reports that require verifiable, official counts of name usage for market research or academic papers.
What Changes When You Connect
Instead of guessing, you get official data. Use get_name_frequency to see exactly how 'Enzo' or 'Maria' surged in popularity during the 2000s.
Need a list of top names? Run get_names_ranking and filter for the best-selling female name in Brazil during the 1980s, instantly.
Writing fiction? Compare multiple names like 'Enzo' and 'Valentina' using their combined data to show how trends overlap or diverge.
The system handles complex filtering. You can combine state IDs with name counts so you know regional preferences—it’s not just national data.
It connects directly to the public IBGE Open Data API, meaning no complicated setup or proprietary keys are required for your agent.
See it in action
A writer needs historical character names.
The writer asks their agent: 'What were the top 10 most popular female names in Bahia during the 1950s?' The agent uses get_names_ranking and provides a vetted, historically accurate list for immediate use.
A sociologist is studying cultural shifts.
The researcher asks their agent to compare 'João' and 'Pedro' across five decades. The agent uses get_name_frequency on both names, revealing a distinct spike in one name that correlates with a known social event.
A data analyst needs multiple comparisons.
The analyst asks their agent to compare the popularity of 'Alex' and 'Bruno' using get_name_frequency. The tool returns side-by-side metrics, allowing for quick identification of shared naming trends.
A content creator needs regional data.
The creator asks their agent to find the top male names only in São Paulo. The agent uses get_names_ranking with a locality filter, giving hyper-specific results that feel authentic.
The honest tradeoffs
Asking for general name popularity.
Just asking 'What are the most popular names in Brazil?' without specifying time or gender. The data is too broad to be useful.
Be specific. Use get_names_ranking and include a filter like 'female' and '1980s'. This narrows the scope down to actionable, verifiable results.
Treating all names as equal.
Listing 20 random names for comparison without knowing if they were popular in the same era. You'll get meaningless data.
Use get_name_frequency and always specify a decade or two adjacent decades to make sure you are comparing apples to apples.
Ignoring regional differences.
Assuming the name 'Ana' is equally popular everywhere in Brazil. The data needs locality context to be accurate.
Always use filters or ask your agent to focus on a specific state ID, which provides localized insights into naming culture.
When It Fits, When It Doesn't
Use this MCP if your project requires verifiable demographic statistics about Brazilian names. Specifically, you need to track frequency changes over time (use get_name_frequency) or generate official lists of common names (use get_names_ranking). Don't use it if you are looking for general naming advice or predicting future trends; the data is historical only. If your goal is merely a quick, rough idea, don't bother with this MCP—it provides authoritative statistics that require specific inputs to be useful.
Questions you might have
How do I use `get_name_frequency` with multiple names? +
You separate the names using a pipe character (|). For example, if you want to compare 'Enzo' and 'Valentina', your query needs to list them as 'ENZO|VALENTINA'.
Is `get_names_ranking` only for national data? +
No. You can filter the ranking results by specific locality IDs (states or municipalities) to understand regional naming preferences.
What time period does IBGE Nomes cover? +
The MCP draws from historical census data, allowing you to check trends across multiple decades of Brazilian history. Always specify the timeframe in your prompt for best results.
Do I need an API key when using `get_name_frequency`? +
No, this MCP uses the public IBGE Open Data API, so you don't have to worry about setting up or managing any keys.
What format should I expect when using `get_names_ranking` or `get_name_frequency`? +
The tools return structured JSON data. Each result includes the name, the decade, and the count of births. This clean structure makes it simple for your agent to parse and present findings.
If I query a name that doesn't exist using `get_name_frequency`, what happens? +
The tool returns an error message indicating the name is not found in the dataset. Always check the API response status codes first to handle these zero-result scenarios gracefully.
Are there limits on how many parameters I can use with `get_names_ranking`? +
While there isn't a strict limit, querying too many filters (e.g., multiple localities and decades) simultaneously may cause timeouts. Keep your inputs focused for the fastest results.
What kind of demographic data is covered by `get_names_ranking`? +
This MCP draws exclusively from historical birth records maintained by IBGE. It tracks name popularity based on recorded births, not other types of census data.
Can I compare the popularity of two different names in the same query? +
Yes! Use the get_name_frequency tool and separate the names with a pipe symbol (e.g., 'MARIA|ANA'). The agent will return the frequency data for both names across the decades.
How do I find the most popular names from the 1990s? +
You can use the get_names_ranking tool and provide '1990' in the decada parameter. This will return a list of the most frequent names recorded during that specific period.
Is it possible to filter name statistics by a specific Brazilian state? +
Absolutely. Both get_name_frequency and get_names_ranking accept a localidade parameter. You just need to provide the IBGE ID for the target state or municipality.
We've already built the connector for IBGE Nomes. Just plug in your AI agents and start using Vinkius.
No hosting. No infrastructure. No complex setup.
All 2 tools are live and waiting.
You're up and running in seconds.
Vinkius gives your AI agents access to the full catalog of app connectors, all fully managed, secure, and enterprise-ready. One subscription, every tool you need.
Built, hosted, and secured by Vinkius. You just connect and go.