IBGE Brasil MCP Server

Live, exact Brazilian public data for your AI assistant — with provenance, not guesswork.

Ask an LLM "what was Belo Horizonte's population in the 2022 Census?" and you get a plausible number from its training data: maybe right, maybe outdated, with no source. ibge-br-mcp instead has your assistant query the official IBGE APIs in real time — returning the exact figure together with the table and period it came from.

🇧🇷 Leia em Português

This server implements the Model Context Protocol (MCP) to give AI assistants live, structured access to Brazil's public geographic, demographic, economic, and health data — sourced from the IBGE APIs (including health indicators served through IBGE's SIDRA system).

See it in action

Ask your assistant, in English or Portuguese:

• "What was Belo Horizonte's population in the 2022 Census?" → ibge_cidades / ibge_censo
• "List the municipalities of Espírito Santo." → ibge_municipios
• "Compare GDP across the Southeast state capitals." → ibge_comparar

The answers come live from the official IBGE APIs — exact figures with the table and period they came from, not numbers guessed from training data.

Want to see a whole analysis rather than a single answer? The end-to-end demo works one real question — which state grew most between the 2010 and 2022 Censuses, and what drove it — from first call to conclusion, with every figure as it came back. The practical examples are seven shorter recipes, including ranking all 5,570 municipalities in a single call.

Features

• 23 tools covering all major IBGE data domains — 21 ibge_* data tools plus search/fetch for ChatGPT Deep Research
• Provenance block on every response — source, canonical URL, reference period, real extraction timestamp, ready-to-use citation, and legal regime (see Data provenance)
• Reference resources & analysis prompts (MCP catalogs + ready-made templates)
• 565 automated tests — 88% overall coverage, 92% across the tools
• Automatic caching with configurable TTL for optimal performance
• Retry mechanism with exponential backoff for network resilience
• Comprehensive validation for all input parameters
• Standardized error handling with helpful suggestions
• Full TypeScript support with strict typing

📖 Article (in Portuguese): Como achar a tabela certa no SIDRA — e como saber que é a certa — finding the right SIDRA table, the metadata that settles it, a full worked example on 2022 Census data, and the four traps that cost the most. Also published on the site, in Portuguese and English: sidneybissoli.com.

🔌 Tutorial: Querying SIDRA through MCP in Claude and ChatGPT — how to connect this server in claude.ai, Claude Desktop, Claude Code, ChatGPT (developer mode and Deep Research), Cursor, VS Code and Gemini CLI, then one real query end to end with the provenance block it returns. Em português.

Data provenance

Since v3.3.0 every successful tool response carries a provenance block (portfolio contract v1.0), so each number is citable, auditable, and reproducible. The block is emitted on three channels:

1. structuredContent.provenance (parseable, visible to the model) — exactly six keys: source (the IBGE API queried), source_url (canonical URL that reproduces the query), data_vintage (reference period when the source exposes one; null otherwise), retrieved_at (the REAL upstream extraction instant, preserved across cache hits, Brasília time), citation ("Fonte: IBGE — [pesquisa/tabela], [URL], extraído em [data]."), and license — plus attribution, the canonical list of source URLs.
2. _meta under br.com.sidneybissoli.ibge/provenance and .../attribution (out-of-band mirror for audit/UI, zero model tokens).
3. A compact text footer appended to the Markdown, for text-only clients.

The IBGE APIs declare no license of their own; the legal regime is Brazil's open-data framework — Lei 12.527/2011 (LAI) and Decreto 8.777/2016 (unrestricted reuse, free use, obligation limited to crediting the source). Statistics-mode responses (estatisticas=true) and ibge_comparar are marked derived with an explanatory note in the canonical block, since the aggregates are computed server-side from the raw IBGE values.

Available Tools

Localities & Geography

Statistical Data (SIDRA)

Economic & Social Indicators

Municipal Data (Cidades@)

International Data

Demographics

Classifications

Maps & Geographic Meshes

Health

News & Calendar

ChatGPT Deep Research

The two are the only tools without the ibge_ prefix: their names are fixed by the OpenAI contract. For data queries keep using the ibge_* tools.

Which tool should I use?

With 23 tools, several can touch the same topic. Quick guide for the common overlaps:

Population & demographics

Economic indicators

Localities & codes

SIDRA workflow

Discover → inspect → query: ibge_pesquisas / ibge_sidra_tabelas (find a table) → ibge_sidra_metadados (its structure) → ibge_sidra (query). For common data, the wrappers above (ibge_censo, ibge_indicadores, ibge_comparar, ibge_cidades) are usually easier.

Maps (meshes)

Installation

Prerequisites

• Node.js 22.x or higher (engines.node)
• npm or yarn

From npm (recommended)

npm install -g ibge-br-mcp

From source

# Clone the repository
git clone https://github.com/SidneyBissoli/ibge-br-mcp.git
cd ibge-br-mcp

# Install dependencies
npm install

# Build the project
npm run build

Configuration

Remote endpoint (nothing to install)

The server is also hosted, with the same tools, over Streamable HTTP and without a key:

https://ibge.sidneybissoli.com/mcp

It works with any client that accepts a remote MCP server — a custom connector in claude.ai (Settings → Connectors → Add custom connector), claude mcp add --transport http ibge https://ibge.sidneybissoli.com/mcp in Claude Code, an app in ChatGPT, the mcp.json of Cursor and VS Code. The step-by-step for each client is in the tutorial. The sections below cover the local form, via npx.

Claude Desktop

Add to your Claude Desktop configuration file (claude_desktop_config.json):

{
  "mcpServers": {
    "ibge-br-mcp": {
      "command": "npx",
      "args": ["-y", "ibge-br-mcp"]
    }
  }
}

Or if installed from source:

{
  "mcpServers": {
    "ibge-br-mcp": {
      "command": "node",
      "args": ["/path/to/ibge-br-mcp/dist/index.js"]
    }
  }
}

Claude Code

{
  "mcpServers": {
    "ibge-br-mcp": {
      "command": "npx",
      "args": ["-y", "ibge-br-mcp"]
    }
  }
}

ChatGPT (Deep Research)

ChatGPT deep research (and company knowledge, and research workflows over the Responses API) only uses an MCP server that exposes exactly search and fetch — this server does, on top of the ibge_* tools. Point the connector at the hosted endpoint, no key required:

https://ibge.sidneybissoli.com/mcp

search ranks the query against SIDRA tables, municipalities and the known indicators and returns { id, title, url }; fetch returns the document as readable Markdown with the canonical public URL (sidra.ibge.gov.br or cidades.ibge.gov.br), which is what ChatGPT cites. Both carry the same provenance block as every other tool. In ChatGPT's developer mode (Settings → Security and login → Developer mode) any tool is callable — the ibge_* tools remain the ones to use for data.

Tool Usage Examples

ibge_estados

List all Brazilian states.

# List all states
ibge_estados

# States in Northeast region
ibge_estados(regiao="NE")

# States sorted by abbreviation
ibge_estados(ordenar="sigla")

ibge_municipios

List Brazilian municipalities.

# Municipalities of São Paulo state
ibge_municipios(uf="SP")

# Search municipalities by name
ibge_municipios(busca="Campinas")

# Municipalities in MG containing "Belo"
ibge_municipios(uf="MG", busca="Belo")

ibge_cidades

Query municipal indicators (similar to Cidades@ portal).

# Panorama of São Paulo
ibge_cidades(tipo="panorama", municipio="3550308")

# Population history
ibge_cidades(tipo="historico", municipio="3550308", indicador="populacao")

# List available research
ibge_cidades(tipo="pesquisas")

Available indicators: populacao, area, densidade, pib_per_capita, idh, escolarizacao, mortalidade, salario_medio, receitas, despesas

ibge_paises

Query international country data.

# List all countries
ibge_paises(tipo="listar")

# Brazil details
ibge_paises(tipo="detalhes", pais="BR")

# Search countries
ibge_paises(tipo="buscar", busca="Argentina")

# Countries in Americas
ibge_paises(tipo="listar", regiao="americas")

Regions: americas, europa, africa, asia, oceania

ibge_sidra

Query SIDRA tables (IBGE's Automatic Recovery System).

# Brazil population in 2023
ibge_sidra(tabela="6579", periodos="2023")

# Population by state
ibge_sidra(tabela="6579", nivel_territorial="3", periodos="2023")

# Census 2022 for São Paulo municipality
ibge_sidra(tabela="9514", nivel_territorial="6", localidades="3550308")

Common tables:

Territorial levels:

Statistics mode (also on ibge_censo, ibge_indicadores, ibge_datasaude): for largest/smallest/mean/median/distribution/ranking questions, pass estatisticas=true — the server computes the full distribution (min/max/mean/ median/std-dev/labeled percentiles) over all rows before pagination and returns top/bottom rankings (topN, default 10). agruparPor="<column label>" ranks groups by descending sum, each with its own mini-distribution.

# Which state has the largest estimated population?
ibge_sidra(tabela="6579", nivel_territorial="3", estatisticas=true)

# Census 2022 population distribution grouped by state
ibge_censo(ano="2022", tema="populacao", nivel_territorial="3", estatisticas=true, agruparPor="Unidade da Federação")

ibge_censo

Query Census data (1970-2022).

# Population Census 2022
ibge_censo(ano="2022", tema="populacao")

# Historical population series
ibge_censo(ano="todos", tema="populacao")

# Literacy by state in 2010
ibge_censo(ano="2010", tema="alfabetizacao", nivel_territorial="3")

Available themes: populacao, alfabetizacao, domicilios, idade_sexo, religiao, cor_raca, rendimento, migracao, educacao, trabalho

ibge_indicadores

Query economic and social indicators.

# GDP
ibge_indicadores(indicador="pib")

# IPCA last 12 months
ibge_indicadores(indicador="ipca", periodos="last 12")

# Unemployment by state
ibge_indicadores(indicador="desemprego", nivel_territorial="3")

# List all indicators
ibge_indicadores(indicador="listar")

Available indicators:

ibge_nomes

Query name frequency and rankings.

# Frequency of "Maria"
ibge_nomes(tipo="frequencia", nomes="Maria")

# Compare names
ibge_nomes(tipo="frequencia", nomes="João,José,Pedro")

# Ranking of names in 2000s
ibge_nomes(tipo="ranking", decada=2000)

# Female names ranking
ibge_nomes(tipo="ranking", sexo="F")

ibge_malhas

Get geographic meshes (maps).

# Brazil with states
ibge_malhas(localidade="BR", resolucao="2")

# São Paulo with municipalities
ibge_malhas(localidade="SP", resolucao="5")

# Specific municipality
ibge_malhas(localidade="3550308")

# SVG format
ibge_malhas(localidade="BR", formato="svg")

Resolution levels:

ibge_datasaude

Query Brazilian health indicators served through IBGE's SIDRA (some originally produced by DataSUS, e.g. mortality and births).

# Infant mortality in Brazil
ibge_datasaude(indicador="mortalidade_infantil")

# Life expectancy by state
ibge_datasaude(indicador="esperanca_vida", nivel_territorial="3")

# List indicators
ibge_datasaude(indicador="listar")

Available indicators: mortalidade_infantil, esperanca_vida, nascidos_vivos, obitos, fecundidade, saneamento_agua, saneamento_esgoto, plano_saude

APIs Used

IBGE APIs

• Localities: servicodados.ibge.gov.br/api/v1/localidades
• Names: servicodados.ibge.gov.br/api/v2/censos/nomes
• Aggregates/SIDRA: servicodados.ibge.gov.br/api/v3/agregados
• SIDRA API: apisidra.ibge.gov.br/values
• Meshes: servicodados.ibge.gov.br/api/v3/malhas
• News: servicodados.ibge.gov.br/api/v3/noticias
• Population: servicodados.ibge.gov.br/api/v1/projecoes/populacao
• CNAE: servicodados.ibge.gov.br/api/v2/cnae
• Calendar: servicodados.ibge.gov.br/api/v3/calendario
• Countries: servicodados.ibge.gov.br/api/v1/paises
• Research: servicodados.ibge.gov.br/api/v1/pesquisas

Development

# Build
npm run build

# Watch mode
npm run watch

# Run tests
npm test

# Run tests in watch mode
npm run test:watch

# Lint
npm run lint

# Format
npm run format

# Test with MCP inspector
npm run inspector

Project Structure

ibge-br-mcp/
├── src/
│   ├── index.ts              # Main MCP server
│   ├── types.ts              # TypeScript types
│   ├── config.ts             # Configuration and constants
│   ├── cache.ts              # Request caching system
│   ├── retry.ts              # Retry with exponential backoff
│   ├── errors.ts             # Standardized error handling
│   ├── validation.ts         # Input validation helpers
│   ├── metrics.ts            # Metrics and logging
│   ├── utils/
│   │   └── formatters.ts     # Formatting utilities
│   └── tools/
│       ├── index.ts          # Tool exports
│       ├── estados.ts        # ibge_estados
│       ├── municipios.ts     # ibge_municipios
│       ├── localidade.ts     # ibge_localidade
│       ├── geocodigo.ts      # ibge_geocodigo
│       ├── censo.ts          # ibge_censo
│       ├── sidra.ts          # ibge_sidra
│       ├── sidra-tabelas.ts  # ibge_sidra_tabelas
│       ├── sidra-metadados.ts# ibge_sidra_metadados
│       ├── indicadores.ts    # ibge_indicadores
│       ├── cnae.ts           # ibge_cnae
│       ├── calendario.ts     # ibge_calendario
│       ├── comparar.ts       # ibge_comparar
│       ├── malhas.ts         # ibge_malhas
│       ├── malhas-tema.ts    # ibge_malhas_tema
│       ├── vizinhos.ts       # ibge_vizinhos
│       ├── datasaude.ts      # ibge_datasaude
│       ├── pesquisas.ts      # ibge_pesquisas
│       ├── nomes.ts          # ibge_nomes
│       ├── noticias.ts       # ibge_noticias
│       ├── paises.ts         # ibge_paises
│       └── cidades.ts        # ibge_cidades
├── tests/                    # Test files
├── dist/                     # Compiled files
├── package.json
├── tsconfig.json
├── vitest.config.ts
└── README.md

Testing

The project includes a comprehensive test suite with 565 tests covering:

• Validation functions
• Retry mechanism
• Formatting utilities
• Error handling
• Cache operations
• Integration tests with mocks

npm test

Quality Assurance

This project maintains high code quality standards:

• 565 automated tests covering validation, caching, retry logic, formatting, and integrations
• 88% overall test coverage — cache and validation modules above 97%
• ESLint for code linting with zero warnings
• Prettier for consistent code formatting
• TypeScript strict mode for type safety
• Automated CI/CD via GitHub Actions

Run tests locally:

# Run all tests
npm test

# Run tests with coverage
npm run test:coverage

# Run linter
npm run lint

License

MIT

Author

Sidney da Silva Pereira Bissoli

References

• IBGE - Data Service
• SIDRA - IBGE Automatic Recovery System
• Model Context Protocol
• MCP TypeScript SDK