# DataJud Scraper (`scrapers_lat/datajud-scraper`) Actor
Extract Brazilian court process records from the CNJ DataJud public database across 90+ federal, state, labor and superior courts. Scrape process number, class, subjects, judging body, filing date and the full timestamped movement timeline.
- **URL**: https://apify.com/scrapers\_lat/datajud-scraper.md
- **Developed by:** [Michael Flores](https://apify.com/scrapers_lat) (community)
- **Categories:** Lead generation, Automation
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet
## Pricing
from $8.00 / 1,000 results
This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.
Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have.
Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event
## What's an Apify Actor?
Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases.
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.
In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md):
```bash
npm install apify-client
```
In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md):
```bash
pip install apify-client
```
In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md):
````bash
# MacOS / Linux
curl -fsSL https://apify.com/install-cli.sh | bash
# Windows
irm https://apify.com/install-cli.ps1 | iex
```bash
In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md).
If your project is in a different language, use 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
## DataJud Scraper
> Extract Brazilian court process records from the CNJ DataJud public database, covering 90+ federal, state, labor and superior court indexes
-blue)
17 fields per record
90+ courts coverage
JSON / CSV / Excel output formats
Updated 2026-06-20
### What you get
Each record is one judicial process from a Brazilian court, including its full timestamped movement timeline, so you can track a case end to end or pull recent processes for a court by class, subject, judging body or filing date.
- **numeroProcesso**: the CNJ process number (20 digits)
- **tribunal**: court code the process belongs to (e.g. TJSP, TRF1, STJ)
- **grau**: instance / degree of jurisdiction (e.g. G1, G2, JE)
- **nivelSigilo**: secrecy level (0 means public)
- **classeCodigo**: procedural class code from the CNJ class table
- **classeNome**: procedural class name
- **sistema**: originating case system (e.g. SAJ, PJe)
- **formato**: process format (Eletrônico or Físico)
- **orgaoJulgadorCodigo**: code of the judging body (chamber / vara)
- **orgaoJulgadorNome**: name of the judging body
- **codigoMunicipioIBGE**: IBGE municipality code of the judging body
- **dataAjuizamento**: filing date and time of the process
- **dataHoraUltimaAtualizacao**: when the record was last updated at the source
- **assuntos**: list of subject codes and names attached to the process
- **movimentos**: full event timeline, each with code, name, timestamp and tabulated complements
- **url**: link to the public CNJ process consultation page
- **observedAt**: when this process was last seen by the scraper
### Who is it for
| Use case | Who benefits |
|---|---|
| KYC and AML litigation checks on a company or person | Compliance and risk teams |
| Building legaltech case-tracking and alerting products | Legal software companies |
| Monitoring case progress across multiple courts | Law firms and in-house counsel |
| Mapping litigation volume by class, subject or region | Legal analysts and researchers |
| Enriching due diligence reports with court history | Investigators and credit bureaus |
### Frequently Asked Questions
**Which Brazilian courts does this cover?**
It queries the CNJ DataJud public API, which exposes more than 90 court indexes: the superior courts (STF, STJ, TST, TSE, STM), the six federal regional courts (TRF1 to TRF6), every state court (TJSP, TJRJ, TJMG and the rest), all 24 labor courts (TRT1 to TRT24) and the state military courts. You pick the court with the tribunal input.
**How many processes can I pull in one run?**
Pagination uses Elasticsearch search_after, so you can collect tens of thousands of processes per run. Set Max Items to cap the count, or leave it open to scan a full filter. The API allows about 120 requests per minute and the actor paces itself to stay within that.
**Can I look up a specific case by its number?**
Yes. Put one or more CNJ process numbers in the Process Numbers field and each is fetched exactly, with its complete movement timeline. If that field is empty, the actor instead returns recent processes for the selected court, narrowed by the filters you set.
**What filters can I apply?**
When querying by court rather than by number, you can filter by class code, subject code, judging body code, and a filing date range. Combine any of them and the actor returns only processes that match all of them.
**Are parties and lawyers included?**
No. The CNJ public API redacts party and lawyer data across every court, so those fields are not available and are not returned. The actor captures everything the public API does expose, including the full movement history.
---
> This actor is an independent tool and has no affiliation with CNJ or the Brazilian judiciary. It only accesses data that is publicly available through the official DataJud public API. Use it in accordance with CNJ's terms of service.
# Actor input Schema
## `maxItems` (type: `integer`):
Maximum number of process records to collect. Optional.
## `tribunal` (type: `string`):
Which court index to query. Each value maps to a DataJud Elasticsearch index (api_publica_).
## `processNumbers` (type: `array`):
Exact process numbers (numeroProcesso, 20 digits, with or without punctuation). Each is looked up exactly. Leave empty to use the filters below instead.
## `classeCode` (type: `integer`):
Filter by procedural class code (TPU/CNJ class table), e.g. 12154 for Execução de Título Extrajudicial. Optional.
## `assuntoCode` (type: `integer`):
Filter by subject/matter code (TPU/CNJ subject table). Optional.
## `orgaoJulgadorCode` (type: `integer`):
Filter by the judging body (court chamber/vara) code. Optional.
## `filedFrom` (type: `string`):
Only processes filed on or after this date (YYYY-MM-DD). Optional.
## `filedTo` (type: `string`):
Only processes filed on or before this date (YYYY-MM-DD). Optional.
## `proxyConfiguration` (type: `object`):
Optional proxy. The DataJud API works from datacenter IPs, so a proxy is not required.
## Actor input object example
```json
{
"maxItems": 10,
"tribunal": "tjsp",
"proxyConfiguration": {
"useApifyProxy": false
}
}
````
# Actor output Schema
## `results` (type: `string`):
No description
# 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 '' with your token
const client = new ApifyClient({
token: '',
});
// Prepare Actor input
const input = {
"maxItems": 10
};
// Run the Actor and wait for it to finish
const run = await client.actor("scrapers_lat/datajud-scraper").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 '' with your token.
client = ApifyClient("")
# Prepare the Actor input
run_input = { "maxItems": 10 }
# Run the Actor and wait for it to finish
run = client.actor("scrapers_lat/datajud-scraper").call(run_input=run_input)
# Fetch and print Actor results from the run's dataset (if there are any)
print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"])
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
print(item)
# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start
```
## CLI example
```bash
echo '{
"maxItems": 10
}' |
apify call scrapers_lat/datajud-scraper --silent --output-dataset
```
## MCP server setup
```json
{
"mcpServers": {
"apify": {
"command": "npx",
"args": [
"mcp-remote",
"https://mcp.apify.com/?tools=scrapers_lat/datajud-scraper",
"--header",
"Authorization: Bearer "
]
}
}
}
```
## OpenAPI specification
```json
{
"openapi": "3.0.1",
"info": {
"title": "DataJud Scraper",
"description": "Extract Brazilian court process records from the CNJ DataJud public database across 90+ federal, state, labor and superior courts. Scrape process number, class, subjects, judging body, filing date and the full timestamped movement timeline.",
"version": "0.1",
"x-build-id": "1fiAO30KD0YtMdtdF"
},
"servers": [
{
"url": "https://api.apify.com/v2"
}
],
"paths": {
"/acts/scrapers_lat~datajud-scraper/run-sync-get-dataset-items": {
"post": {
"operationId": "run-sync-get-dataset-items-scrapers_lat-datajud-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK"
}
}
}
},
"/acts/scrapers_lat~datajud-scraper/runs": {
"post": {
"operationId": "runs-sync-scrapers_lat-datajud-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor and returns information about the initiated run in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK",
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/runsResponseSchema"
}
}
}
}
}
}
},
"/acts/scrapers_lat~datajud-scraper/run-sync": {
"post": {
"operationId": "run-sync-scrapers_lat-datajud-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK"
}
}
}
}
},
"components": {
"schemas": {
"inputSchema": {
"type": "object",
"properties": {
"maxItems": {
"title": "Max Items",
"minimum": 1,
"maximum": 1000000,
"type": "integer",
"description": "Maximum number of process records to collect. Optional."
},
"tribunal": {
"title": "Court (tribunal)",
"enum": [
"stf",
"stj",
"tst",
"tse",
"stm",
"trf1",
"trf2",
"trf3",
"trf4",
"trf5",
"trf6",
"tjsp",
"tjrj",
"tjmg",
"tjrs",
"tjpr",
"tjba",
"tjsc",
"tjgo",
"tjpe",
"tjce",
"tjdft",
"tjes",
"tjpa",
"tjmt",
"tjms",
"tjpb",
"tjrn",
"tjal",
"tjpi",
"tjse",
"tjma",
"tjto",
"tjro",
"tjam",
"tjac",
"tjap",
"tjrr",
"trt1",
"trt2",
"trt3",
"trt4",
"trt5",
"trt6",
"trt7",
"trt8",
"trt9",
"trt10",
"trt11",
"trt12",
"trt13",
"trt14",
"trt15",
"trt16",
"trt17",
"trt18",
"trt19",
"trt20",
"trt21",
"trt22",
"trt23",
"trt24",
"tjmmg",
"tjmrs",
"tjmsp"
],
"type": "string",
"description": "Which court index to query. Each value maps to a DataJud Elasticsearch index (api_publica_).",
"default": "tjsp"
},
"processNumbers": {
"title": "Process numbers",
"type": "array",
"description": "Exact process numbers (numeroProcesso, 20 digits, with or without punctuation). Each is looked up exactly. Leave empty to use the filters below instead.",
"items": {
"type": "string"
}
},
"classeCode": {
"title": "Class code (classe.codigo)",
"type": "integer",
"description": "Filter by procedural class code (TPU/CNJ class table), e.g. 12154 for Execução de Título Extrajudicial. Optional."
},
"assuntoCode": {
"title": "Subject code (assuntos.codigo)",
"type": "integer",
"description": "Filter by subject/matter code (TPU/CNJ subject table). Optional."
},
"orgaoJulgadorCode": {
"title": "Judging body code (orgaoJulgador.codigo)",
"type": "integer",
"description": "Filter by the judging body (court chamber/vara) code. Optional."
},
"filedFrom": {
"title": "Filed from (dataAjuizamento)",
"type": "string",
"description": "Only processes filed on or after this date (YYYY-MM-DD). Optional."
},
"filedTo": {
"title": "Filed to (dataAjuizamento)",
"type": "string",
"description": "Only processes filed on or before this date (YYYY-MM-DD). Optional."
},
"proxyConfiguration": {
"title": "Proxy configuration",
"type": "object",
"description": "Optional proxy. The DataJud API works from datacenter IPs, so a proxy is not required.",
"default": {
"useApifyProxy": false
}
}
}
},
"runsResponseSchema": {
"type": "object",
"properties": {
"data": {
"type": "object",
"properties": {
"id": {
"type": "string"
},
"actId": {
"type": "string"
},
"userId": {
"type": "string"
},
"startedAt": {
"type": "string",
"format": "date-time",
"example": "2025-01-08T00:00:00.000Z"
},
"finishedAt": {
"type": "string",
"format": "date-time",
"example": "2025-01-08T00:00:00.000Z"
},
"status": {
"type": "string",
"example": "READY"
},
"meta": {
"type": "object",
"properties": {
"origin": {
"type": "string",
"example": "API"
},
"userAgent": {
"type": "string"
}
}
},
"stats": {
"type": "object",
"properties": {
"inputBodyLen": {
"type": "integer",
"example": 2000
},
"rebootCount": {
"type": "integer",
"example": 0
},
"restartCount": {
"type": "integer",
"example": 0
},
"resurrectCount": {
"type": "integer",
"example": 0
},
"computeUnits": {
"type": "integer",
"example": 0
}
}
},
"options": {
"type": "object",
"properties": {
"build": {
"type": "string",
"example": "latest"
},
"timeoutSecs": {
"type": "integer",
"example": 300
},
"memoryMbytes": {
"type": "integer",
"example": 1024
},
"diskMbytes": {
"type": "integer",
"example": 2048
}
}
},
"buildId": {
"type": "string"
},
"defaultKeyValueStoreId": {
"type": "string"
},
"defaultDatasetId": {
"type": "string"
},
"defaultRequestQueueId": {
"type": "string"
},
"buildNumber": {
"type": "string",
"example": "1.0.0"
},
"containerUrl": {
"type": "string"
},
"usage": {
"type": "object",
"properties": {
"ACTOR_COMPUTE_UNITS": {
"type": "integer",
"example": 0
},
"DATASET_READS": {
"type": "integer",
"example": 0
},
"DATASET_WRITES": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_READS": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_WRITES": {
"type": "integer",
"example": 1
},
"KEY_VALUE_STORE_LISTS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_READS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_WRITES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_INTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_EXTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_SERPS": {
"type": "integer",
"example": 0
}
}
},
"usageTotalUsd": {
"type": "number",
"example": 0.00005
},
"usageUsd": {
"type": "object",
"properties": {
"ACTOR_COMPUTE_UNITS": {
"type": "integer",
"example": 0
},
"DATASET_READS": {
"type": "integer",
"example": 0
},
"DATASET_WRITES": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_READS": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_WRITES": {
"type": "number",
"example": 0.00005
},
"KEY_VALUE_STORE_LISTS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_READS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_WRITES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_INTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_EXTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_SERPS": {
"type": "integer",
"example": 0
}
}
}
}
}
}
}
}
}
}
```