# SidneyBissoli/ibge-br-mcp [Health: Active]

**Category:** 🗄️ Databases  
**Repository:** https://github.com/SidneyBissoli/ibge-br-mcp  
**GitHub Stars:** 9  
**npm Downloads (last month):** 1385  
**Views:** 2  
**Installs:** 0  
**Upvotes:** 0  
**Directory Page:** https://allmcps.com/mcp/sidneybissoli-ibge-br-mcp

## Description
Brazilian Census Bureau (IBGE) data server with 23 tools for demographics, geography, economics, and statistics. Covers localities, SIDRA tables, Census data, population projections, and geographic meshes.

## Tools
Capabilities this server exposes over MCP:

- **ibge_estados** — List Brazilian states with region filtering
- **ibge_municipios** — List municipalities by state or search by name
- **ibge_localidade** — Get details of a locality by IBGE code
- **ibge_geocodigo** — Decode IBGE codes or search codes by name
- **ibge_vizinhos** — Find neighboring municipalities
- **ibge_sidra** — Query SIDRA tables (Census, PNAD, GDP, etc.)
- **ibge_sidra_tabelas** — List and search available SIDRA tables
- **ibge_sidra_metadados** — Get table metadata (variables, periods, levels)
- **ibge_pesquisas** — List IBGE research surveys and their tables
- **ibge_indicadores** — Economic and social indicators (GDP, IPCA, unemployment)
- **ibge_censo** — Census data (1970-2022) with 16 themes
- **ibge_comparar** — Compare indicators across localities with rankings
- **ibge_cidades** — Municipal indicators (population, HDI, GDP per capita, etc.)
- **ibge_paises** — Country data following UN M49 methodology
- **ibge_populacao** — Real-time Brazilian population projection
- **ibge_nomes** — Name frequency and rankings in Brazil
- **ibge_cnae** — CNAE (National Classification of Economic Activities)
- **ibge_malhas** — Geographic meshes (GeoJSON, TopoJSON, SVG)
- **ibge_malhas_tema** — Thematic meshes (biomes, Legal Amazon, semi-arid)
- **ibge_datasaude** — Health indicators via IBGE's SIDRA
- **ibge_noticias** — IBGE news and press releases
- **ibge_calendario** — IBGE release and collection calendar

## Claude Desktop Quick Installation
Install path detected from listing signals. Uses `npx` (confidence: high):

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

## Documentation & README

# IBGE Brasil MCP Server

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**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](https://github.com/SidneyBissoli/ibge-br-mcp/blob/HEAD/README.pt-BR.md)

This server implements the [Model Context Protocol (MCP)](https://modelcontextprotocol.io/) 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**](https://github.com/SidneyBissoli/ibge-br-mcp/blob/HEAD/docs/demo.md) 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**](https://github.com/SidneyBissoli/ibge-br-mcp/blob/HEAD/examples/README.md) 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](#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](https://github.com/SidneyBissoli/ibge-br-mcp/blob/HEAD/docs/artigo-sidra-tabela-certa.pt-BR.md) — 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](https://sidneybissoli.com/en/blog/posts/sidra-tabela-certa/).

🔌 **Tutorial:** [Querying SIDRA through MCP in Claude and ChatGPT](https://sidneybissoli.com/en/blog/posts/sidra-via-mcp/) — 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](https://sidneybissoli.com/blog/posts/sidra-via-mcp/).

## Data provenance

Since v3.3.0 every successful tool response carries a **provenance block**
([portfolio contract v1.0](https://www.npmjs.com/package/@sbissoli/mcp-provenance)),
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
| Tool | Description |
|:-----|:------------|
| `ibge_estados` | List Brazilian states with region filtering |
| `ibge_municipios` | List municipalities by state or search by name |
| `ibge_localidade` | Get details of a locality by IBGE code |
| `ibge_geocodigo` | Decode IBGE codes or search codes by name |
| `ibge_vizinhos` | Find neighboring municipalities |

### Statistical Data (SIDRA)
| Tool | Description |
|:-----|:------------|
| `ibge_sidra` | Query SIDRA tables (Census, PNAD, GDP, etc.) |
| `ibge_sidra_tabelas` | List and search available SIDRA tables |
| `ibge_sidra_metadados` | Get table metadata (variables, periods, levels) |
| `ibge_pesquisas` | List IBGE research surveys and their tables |

### Economic & Social Indicators
| Tool | Description |
|:-----|:------------|
| `ibge_indicadores` | Economic and social indicators (GDP, IPCA, unemployment) |
| `ibge_censo` | Census data (1970-2022) with 16 themes |
| `ibge_comparar` | Compare indicators across localities with rankings |

### Municipal Data (Cidades@)
| Tool | Description |
|:-----|:------------|
| `ibge_cidades` | Municipal indicators (population, HDI, GDP per capita, etc.) |

### International Data
| Tool | Description |
|:-----|:------------|
| `ibge_paises` | Country data following UN M49 methodology |

### Demographics
| Tool | Description |
|:-----|:------------|
| `ibge_nomes` | Name frequency and rankings in Brazil |

### Classifications
| Tool | Description |
|:-----|:------------|
| `ibge_cnae` | CNAE (National Classification of Economic Activities) |

### Maps & Geographic Meshes
| Tool | Description |
|:-----|:------------|
| `ibge_malhas` | Geographic meshes (GeoJSON, TopoJSON, SVG) |
| `ibge_malhas_tema` | What a thematic recorte contains (biomes, Legal Amazon, semi-arid, coastal, border strip, metro regions, RIDEs) + the URL to download its geometry |

### Health
| Tool | Description |
|:-----|:------------|
| `ibge_datasaude` | Health indicators via IBGE's SIDRA |

### News & Calendar
| Tool | Description |
|:-----|:------------|
| `ibge_noticias` | IBGE news and press releases |
| `ibge_calendario` | IBGE release and collection calendar |

### ChatGPT Deep Research
| Tool | Description |
|:-----|:------------|
| `search` | Searches the IBGE catalog (SIDRA tables, municipalities, known indicators) — OpenAI Deep Research contract |
| `fetch` | Returns one catalog document (table metadata, municipality hierarchy + population, indicator series) with its public URL for citation |

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

| You want… | Use |
|:----------|:----|
| A single municipality/state panel (population, HDI, GDP…) | `ibge_cidades` |
| Census data or historical series (1970–2022) | `ibge_censo` |
| Rank/compare 2–10 localities on one indicator | `ibge_comparar` |
| A macro indicator time series (GDP, IPCA, unemployment…) | `ibge_indicadores` |
| A specific SIDRA table / fine control | `ibge_sidra` |
| The largest/smallest/mean/median across a whole table | `ibge_sidra`/`ibge_censo`/`ibge_indicadores`/`ibge_datasaude` with `estatisticas=true` |

### Economic indicators

| You want… | Use |
|:----------|:----|
| IPCA, INPC, GDP, unemployment (IBGE, primary source) | `ibge_indicadores` |

### Localities & codes

| You want… | Use |
|:----------|:----|
| List/search municipalities | `ibge_municipios` |
| List states | `ibge_estados` |
| Resolve a name→code at any level, or decode a code's structure | `ibge_geocodigo` |
| Full record of one locality you already have the code for | `ibge_localidade` |
| Neighboring municipalities | `ibge_vizinhos` |

### 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)

| You want… | Use |
|:----------|:----|
| Administrative outlines (Brazil/region/state/municipality) | `ibge_malhas` |
| Thematic areas (biomes, Legal Amazon, semi-arid, metro regions) | `ibge_malhas_tema` (IBGE Geosserviços WFS — the Malhas API does not publish these) |

## Installation

### Prerequisites

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

### From npm (recommended)

```bash
npm install -g ibge-br-mcp
```

### From source

```bash
# 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](https://sidneybissoli.com/en/blog/posts/sidra-via-mcp/). The sections below cover the local form, via `npx`.

### Claude Desktop

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

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

Or if installed from source:

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

### Claude Code

```json
{
  "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:**
| Code | Description |
|-----:|:------------|
| 6579 | Population estimates (annual) |
| 9514 | Census 2022 population |
| 4714 | Unemployment rate (PNAD) |
| 6706 | GDP at current prices |

**Territorial levels:**
| Code | Level |
|-----:|:------|
| 1 | Brazil |
| 2 | Region (North, Northeast, etc.) |
| 3 | State (UF) |
| 6 | Municipality |
| 7 | Metropolitan Region |
| 106 | Health Region |
| 127 | Legal Amazon |
| 128 | Semi-arid |

**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:**
| Category | Indicators |
|:---------|:-----------|
| Economic | pib, pib_variacao, pib_per_capita, industria, comercio, servicos |
| Prices | ipca, ipca_acumulado, inpc |
| Labor | desemprego, ocupacao, rendimento, informalidade |
| Population | populacao, densidade |
| Agriculture | agricultura, pecuaria |

### 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:**
| Value | Internal Divisions |
|:-----:|:-------------------|
| 0 | No divisions (outline only) |
| 2 | States |
| 5 | Municipalities |

### 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

```bash
# 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

```bash
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:
```bash
# 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](https://servicodados.ibge.gov.br/api/docs/)
- [SIDRA - IBGE Automatic Recovery System](https://sidra.ibge.gov.br/)
- [Model Context Protocol](https://modelcontextprotocol.io/)
- [MCP TypeScript SDK](https://github.com/modelcontextprotocol/typescript-sdk)