IBGE SIDRA MCP for AI. Analyze Brazil's Official Economic Indicators
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IBGE Agregados (SIDRA) gives you direct access to Brazil's official statistical databases. Use this MCP to query demographic and economic data from IBGE SIDRA, allowing your agent to search for specific surveys, check metadata details, find available variables, or map geographic levels without navigating complex web portals.
What your AI can do
Get localidades
Retrieves all geographic levels (like state or city) available for a specified data aggregate.
Get metadados
Fetches the complete documentation and context rules for any specific statistical table.
Get periodos
Determines which time ranges or years of data are available for a given survey.
You can list and filter all IBGE aggregates (surveys/tables) by subject or classification.
Retrieve detailed metadata for any specific aggregate to understand its methodology and scope.
List all variables available within a chosen aggregate, ensuring you select the right metrics before querying.
Determine which historical or future periods are available for any given survey.
See every territorial level, from national to municipal, that a specific dataset supports.
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IBGE Agregados (SIDRA) Has 5 Tools
Use these five specialized tools to find the exact datasets, metrics, time ranges, and location levels needed for complex Brazilian statistical analysis.
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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 Agregados (SIDRA) on VinkiusGet Localidades
Retrieves all geographic levels (like state or city) available for a specified data aggregate.
Get Metadados
Fetches the complete documentation and context rules for any specific statistical...
Get Periodos
Determines which time ranges or years of data are available for a given survey.
Get Variaveis
Lists every single measurable variable (the columns) that the chosen dataset...
List Agregados
Allows you to search and list available statistical surveys or tables by topic.
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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by IBGE Agregados (SIDRA). 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.
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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 5 powerful capabilities that interface natively with Claude, ChatGPT, Cursor, and other compatible AI platforms. No middleware. No custom integration required.
Dealing with Bureaucracy and Dead Links
Today, getting official statistics means navigating dozens of government websites. You click through portals just to find an aggregate ID, then you download a PDF, and finally, you copy-paste variables into your spreadsheet—a process that eats up half a day.
With this MCP, the whole sequence becomes conversational. Your agent finds the right table ID using `list_agregados`, confirms its scope with metadata, and gets ready to query the data—all without opening a browser tab.
Accessing Official Data With IBGE Agregados (SIDRA)
The manual steps that disappear are: navigating complex URL structures, cross-referencing multiple documentation pages to find a variable ID, and manually checking which geographic levels the data supports.
Now you get predictable, structured access. You ask for what you want, and the tool guides your agent through confirming every required parameter before delivering clean statistical results.
What your AI can actually do with this
Accessing Brazilian statistics used to mean days lost clicking through convoluted government websites. Now, you can speak in natural language and get exactly what you need from the official IBGE SIDRA database. This MCP lets your agent talk directly to the source of Brazil’s demographic and economic data.
Instead of manually figuring out which tables exist or what variables are available for a specific survey, you simply ask. The system handles the complexity of locating the right aggregate IDs and checking the required parameters—whether that's confirming the correct time period or identifying the necessary regional level. All this power is housed within Vinkius, making it easy to connect to your preferred AI client.
It’s about moving from manual data hunting to direct statistical query execution.
019e38ab-a68a-730f-b551-ae214b5ba7c0 Here's how it actually works
The bottom line is, it takes messy manual steps of cross-referencing web documentation and turns them into a simple, multi-step query sequence.
First, use the MCP to list available aggregates to find the ID of the survey you need.
Next, query the metadata and variable tools using that aggregate ID to confirm data context, time periods, and location levels.
Finally, your agent executes the complex statistical retrieval based on all confirmed parameters.
Who is this actually for?
Data Scientists and researchers who rely on official Brazilian economic data. If your job involves comparing census figures or modeling regional growth using government stats, this is for you. It cuts out the bureaucratic friction of accessing public sector data.
You use it to compare historical GDP trends across different Brazilian states by cross-referencing time periods and regional levels.
You run complex data pipelines, needing the agent to automatically fetch variable lists (get_variaveis) before writing a final analysis script.
You verify study parameters by running get_metadados on an aggregate ID to confirm the exact methodology and scope used in the original census.
What Changes When You Connect
Instead of guessing which ID to query, use list_agregados to filter and find the exact survey you need based on your topic or time frame.
Avoid data errors by first running get_metadados. This tool gives you the necessary context and rules for the dataset, so you know if the data is suitable for modeling.
You can build historical series easily. By checking available time periods with get_periodos, your agent confirms the full temporal scope before building a report.
Precision matters in stats. Use get_variaveis to get a definitive list of all metrics, ensuring you only query for existing columns and avoiding data gaps.
Never worry about geography again. get_localidades tells you immediately if the dataset covers municipal levels or just state-level summaries.
See it in action
Modeling regional economic shifts
A user needs to compare employment rates across five Brazilian states over the last decade. They first run list_agregados to find the correct labor survey ID, then call get_variaveis for 'employment' and get_localidades to confirm all five states are included before running the final query.
Verifying research scope
A researcher needs to write a paper citing specific census data. They use get_metadados on an aggregate ID to ensure they understand the exact date, methodology, and limitations of the source material before including it in their bibliography.
Building time-series dashboards
A developer needs to display a variable's trend over 20 years. They first check get_periodos for available dates, confirm the necessary variables via get_variaveis, and then build the visualization using the confirmed data range.
The honest tradeoffs
Asking for vague statistics
Just prompting: 'Give me Brazil’s GDP.' The agent fails because it doesn't know which specific aggregate ID or variable to target.
Start by using list_agregados to narrow down the topic (e.g., 'PIB'). Then, use that resulting ID with get_variaveis to select the precise metric you need.
Assuming data coverage
Writing code assuming a dataset covers all Brazilian states when it might only cover major metropolitan areas.
Always run get_localidades first. This confirms if the specific aggregate supports the geographic granularity you need before writing any query logic.
Ignoring data rules
Running a complex query without knowing if the variables are comparable across different time periods.
Call get_metadados immediately. This reveals the underlying methodology and limitations, preventing you from mixing incompatible datasets.
When It Fits, When It Doesn't
Use this MCP if your data needs to be official Brazilian statistics (IBGE SIDRA) and requires multiple layers of filtering—you need to confirm the aggregate ID, then check variables, periods, AND locations. Don't use it if you just need general demographic facts or simple country averages; those are usually found in simpler data tools. Never skip get_metadados when starting a new analysis; that tool is your safety net for understanding the source material's limitations.
Questions you might have
How can I find specific surveys related to a topic like 'Employment'? +
Use the list_agregados tool and provide a keyword in the assunto parameter. The agent will return a list of all relevant aggregate tables and their IDs.
Can I see which years or months are available for a specific table ID? +
Yes! By using the get_periodos tool with the specific Aggregate ID, you can retrieve all available time intervals for that dataset.
How do I know if a table has data at the city level (municípios)? +
Run the get_localidades tool for the target Aggregate ID. It will list all supported geographic levels, such as 'Brasil', 'Unidade da Federação', or 'Município'.
How do I check what data fields are available for a specific aggregate? Should I use get_variaveis? +
Yes, running get_variaveis pulls the complete list of variables for any given aggregate. This is key because it gives you the exact IDs and names needed to structure your precise queries before fetching the actual data.
I need data that combines several different subjects (e.g., labor force and industry). How do I filter those results? +
Use list_agregados for advanced filtering. You can apply multidimensional criteria, narrowing down the search by subject, classification, or period to pinpoint specific tables across IBGE's vast dataset.
I found a table ID but I don’t know what the data means; is there a way to understand its context? +
Calling get_metadados retrieves the full documentation for that aggregate. This step is crucial because it explains the methodology, definitions, and precise scope of the statistical data you're dealing with.
Do I need to worry about complex API keys or authentication before starting queries? +
No, this MCP service functions as a public data resource. You don't need custom credentials; just connect your AI agent through the Vinkius marketplace to start querying immediately.
If I run multiple checks—like checking get_localidades and get_variaveis—will there be rate limits? +
The system handles standard query volumes efficiently. If you plan on batch processing massive amounts of data, always check Vinkius's usage guidelines to ensure your workflow stays within optimal operational parameters.
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