# My Actor (`bantam_shovel/my-actor`) Actor

- **URL**: https://apify.com/bantam\_shovel/my-actor.md
- **Developed by:** [Marcos Aurelio](https://apify.com/bantam_shovel) (community)
- **Categories:**
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

Pay per usage

This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-usage

## What's an Apify Actor?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.
Actors are written with capital "A".

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.
The best way to integrate Actors is as follows.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — the [REST API](https://docs.apify.com/api/v2.md).

For usage examples, see the [API](#api) section below.

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).

# README

## Brasil CEP para Endereco - Apify Actor

Actor da Apify que recebe um ou varios CEPs brasileiros e devolve enderecos estruturados. A consulta usa o endpoint CEP v2 da [BrasilAPI](https://brasilapi.com.br/), projeto open source mantido em [github.com/BrasilAPI/BrasilAPI](https://github.com/BrasilAPI/BrasilAPI).

### Entrada

```json
{
  "ceps": ["01001-000", "30130-010"],
  "maxConcurrency": 5,
  "timeoutSecs": 10,
  "maxRetries": 2,
  "failOnError": false
}
```

- `ceps`: de 1 a 1.000 CEPs, com ou sem pontuacao.
- `maxConcurrency`: consultas simultaneas, entre 1 e 20.
- `timeoutSecs`: tempo limite de cada tentativa.
- `maxRetries`: repeticoes para erros temporarios (HTTP 429/5xx ou rede).
- `failOnError`: faz a execucao falhar caso algum CEP nao seja resolvido; os resultados ainda sao salvos.

### Saida

Cada CEP gera um item no dataset:

```json
{
  "inputCep": "01001-000",
  "success": true,
  "cep": "01001-000",
  "street": "Praca da Se",
  "neighborhood": "Se",
  "city": "Sao Paulo",
  "state": "SP",
  "fullAddress": "Praca da Se, Se, Sao Paulo - SP, CEP 01001-000, Brasil",
  "latitude": -23.5505,
  "longitude": -46.6333,
  "service": "open-cep",
  "error": null
}
```

O registro `OUTPUT` do key-value store contem um resumo com `total`, `succeeded`, `failed` e `finishedAt`.

### Executar localmente

Requisitos: Node.js 22 ou superior.

```bash
npm install
npm test
npm start
```

A entrada local fica em `storage/key_value_stores/default/INPUT.json`.

### Publicar a partir do GitHub

1. Crie um repositorio no GitHub e envie estes arquivos.
2. Na Apify Console, crie um Actor e escolha **Git repository** como origem.
3. Informe a URL do repositorio e use `Dockerfile` como arquivo de build.
4. Execute o build e teste com um CEP conhecido.

Tambem e possivel instalar a [Apify CLI](https://docs.apify.com/cli) e publicar diretamente com `apify push`.

### Observacoes

- CEPs invalidos ou nao encontrados geram itens com `success: false`; o lote continua.
- A disponibilidade e a cobertura dos dados dependem da BrasilAPI e de seus provedores.
- O Actor nao exige token da BrasilAPI.

# Actor input Schema

## `ceps` (type: `array`):

Lista de CEPs brasileiros, com 8 digitos cada.

## `maxConcurrency` (type: `integer`):

Quantidade maxima de CEPs consultados ao mesmo tempo.

## `timeoutSecs` (type: `integer`):

Tempo limite, em segundos, para cada tentativa.

## `maxRetries` (type: `integer`):

Numero de novas tentativas para falhas temporarias.

## `failOnError` (type: `boolean`):

Quando ativo, o Actor termina com erro apos salvar todos os resultados.

## Actor input object example

```json
{
  "ceps": [
    "01001-000"
  ],
  "maxConcurrency": 5,
  "timeoutSecs": 10,
  "maxRetries": 2,
  "failOnError": false
}
```

# Actor output Schema

## `addresses` (type: `string`):

Itens de endereco, um por CEP informado.

## `summary` (type: `string`):

Totais de consultas bem-sucedidas e com erro.

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {};

// Run the Actor and wait for it to finish
const run = await client.actor("bantam_shovel/my-actor").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {}

# Run the Actor and wait for it to finish
run = client.actor("bantam_shovel/my-actor").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{}' |
apify call bantam_shovel/my-actor --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,bantam_shovel/my-actor"
        }
    }
}

```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/IrdXs6DRtl9E2Ye12/builds/sszOxxxHai7fJVcJ5/openapi.json