# Tool: Any Text to Structured JSON (`scrapers_lat/text-to-json-tool`) Actor
Convert any unstructured text into clean structured JSON that matches the schema you define, using premium AI. Paid Apify plans only.
- **URL**: https://apify.com/scrapers\_lat/text-to-json-tool.md
- **Developed by:** [Scrapers Lat](https://apify.com/scrapers_lat) (community)
- **Categories:** AI, Developer tools, Automation
- **Stats:** 2 total users, 1 monthly users, 75.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet
## Pricing
from $64.00 / 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
[](https://console.apify.com/actors/text-to-json-tool)
## Tool: Any Text to Structured JSON
> Turn messy, unstructured text into clean JSON that matches the schema you define. Describe the fields you want and get one structured record per text.
Your schema define the fields you want
Any text in emails, listings, notes
JSON / CSV / Excel output formats
### What it does
Give it a list of texts and a schema that names the fields you want. For each text it returns one clean JSON object matching your fields:
- Every key from your **schema**, filled from the text or set to null when not present
- A **_sourceIndex** so you can line each record up with its input
- **observedAt** timestamp on every record
Use it to pull prices, names, dates, order numbers, addresses and any other fields out of free-form text without writing regex or parsers. Export to JSON, CSV or Excel, or pull it through the Apify API.
### Paid plans only
This tool runs on the latest, most reliable premium AI models. Because each run has a real model cost, it is available to paid Apify accounts only. A run started from a free account stops immediately with an upgrade message. Upgrade your Apify subscription to a paid plan and run it again.
### Who is it for
| Use case | Who benefits |
|---|---|
| Data teams | Turning notes and emails into rows |
| Developers | Skipping one-off parsers and regex |
| Ops | Normalizing supplier or order text |
| Research | Structuring survey and interview replies |
### Input
- **texts**: a list of items, each a plain string or `{ "text": "..." }`.
- **schema**: a JSON object naming the fields to extract, for example `{ "name": "", "price": "", "date": "" }`.
- **maxItems**: optional cap on how many texts to convert this run.
### Notes
- Fields that are not in a text come back as null. The tool does not invent values.
- Long texts are trimmed to a safe length before conversion, and the record marks when that happened.
### FAQ
**How do I define the schema?**
Pass a JSON object where each key is a field you want back. The values can be empty strings or short examples.
**What if I do not pass a schema?**
The tool infers the most useful fields from each text and returns them as a flat object.
**Can I convert many texts at once?**
Yes. Pass an array and each text returns its own record, tagged with its source index.
### Example use cases
Ready-to-run example tasks, each preconfigured for a common scenario. Open one and press run, or use it as a template:
- [Parse a Shipping Address into JSON](https://apify.com/scrapers_lat/text-to-json-tool/examples/t2j-parse-shipping-address-to-json): Turn a messy one line address into clean JSON fields for street, city, state and zip so your orders import without errors.
- [Parse an Invoice Line into JSON](https://apify.com/scrapers_lat/text-to-json-tool/examples/t2j-parse-invoice-line-to-json): Extract product, quantity, unit price and total from an invoice line into structured JSON for faster bookkeeping.
- [Parse an Order Line into JSON](https://apify.com/scrapers_lat/text-to-json-tool/examples/t2j-parse-order-line-to-json): Convert free text order lines into JSON with SKU, size and color so ecommerce systems process them without manual entry.
- [Parse Business Card Text into JSON](https://apify.com/scrapers_lat/text-to-json-tool/examples/t2j-parse-business-card-to-json): Turn scanned business card text into JSON contact fields for name, title, company, email and phone to fill your CRM fast.
- [Parse Event Details into JSON](https://apify.com/scrapers_lat/text-to-json-tool/examples/t2j-parse-event-details-to-json): Extract event name, date, time and venue from a text invite into JSON so calendars and booking tools stay accurate.
- [Parse a Job Posting Snippet into JSON](https://apify.com/scrapers_lat/text-to-json-tool/examples/t2j-parse-job-posting-to-json): Structure a job posting snippet into JSON with title, company, location and salary so recruiters compare roles quickly.
- [Parse Recipe Ingredients into JSON](https://apify.com/scrapers_lat/text-to-json-tool/examples/t2j-parse-recipe-ingredient-to-json): Break recipe ingredient lines into JSON with amount, unit and item so meal apps and shopping lists stay consistent.
- [Parse a Real Estate Listing into JSON](https://apify.com/scrapers_lat/text-to-json-tool/examples/t2j-parse-real-estate-listing-to-json): Turn a property listing sentence into JSON with beds, baths, price and location so agents load data into portals faster.
- [Parse a Flight Itinerary into JSON](https://apify.com/scrapers_lat/text-to-json-tool/examples/t2j-parse-flight-itinerary-to-json): Extract airline, flight number, origin, destination and time from an itinerary line into JSON for travel tools.
- [Parse Customer Feedback into JSON](https://apify.com/scrapers_lat/text-to-json-tool/examples/t2j-parse-customer-feedback-to-json): Structure open customer feedback into JSON with product, issue and rating so support teams track themes without tagging by hand.
### Export, API and AI agents (x402 + MCP)
Export the scraped data to **JSON, CSV or Excel**, pull it as a **dataset** through the Apify **API**, or wire it into your app with **no code**. This web scraper and data extractor also works for bulk data extraction and scheduled runs.
For AI agents: this Actor is available on **x402**, Apify's agentic payment standard built with Coinbase. An AI agent can discover, pay for and run it on its own with a funded wallet and a single HTTP request: no account, no subscription, no API key and no human in the loop. It also runs as an **MCP** tool inside Claude, Cursor and other AI clients out of the box. Learn more about [x402 agentic payments on Apify](https://docs.apify.com/platform/integrations/x402).
Built by [scrapers.lat](https://scrapers.lat).
# Actor input Schema
## `texts` (type: `array`):
A list of texts to turn into JSON. Each item is either a plain string or an object with a text field. Provide one item per record you want back.
## `schema` (type: `object`):
A JSON object describing the fields to extract. Keys are the field names you want, values are examples or empty strings. The tool returns one object per text matching these keys.
## `maxItems` (type: `integer`):
Cap how many texts to convert this run. Optional.
## Actor input object example
```json
{
"texts": [
"Order #10493 for Maria Lopez shipped on 2026-06-12. Total charged was 148.50 USD for a Herman Miller Aeron chair.",
"New listing: 2019 Toyota Corolla LE, 42,000 miles, priced at 17,900 dollars, located in Austin TX. Contact seller at (512) 555-0142."
],
"schema": {
"name": "",
"price": "",
"date": ""
}
}
````
# 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 = {
"texts": [
"Order #10493 for Maria Lopez shipped on 2026-06-12. Total charged was 148.50 USD for a Herman Miller Aeron chair.",
"New listing: 2019 Toyota Corolla LE, 42,000 miles, priced at 17,900 dollars, located in Austin TX. Contact seller at (512) 555-0142."
],
"schema": {
"name": "",
"price": "",
"date": ""
}
};
// Run the Actor and wait for it to finish
const run = await client.actor("scrapers_lat/text-to-json-tool").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 = {
"texts": [
"Order #10493 for Maria Lopez shipped on 2026-06-12. Total charged was 148.50 USD for a Herman Miller Aeron chair.",
"New listing: 2019 Toyota Corolla LE, 42,000 miles, priced at 17,900 dollars, located in Austin TX. Contact seller at (512) 555-0142.",
],
"schema": {
"name": "",
"price": "",
"date": "",
},
}
# Run the Actor and wait for it to finish
run = client.actor("scrapers_lat/text-to-json-tool").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 '{
"texts": [
"Order #10493 for Maria Lopez shipped on 2026-06-12. Total charged was 148.50 USD for a Herman Miller Aeron chair.",
"New listing: 2019 Toyota Corolla LE, 42,000 miles, priced at 17,900 dollars, located in Austin TX. Contact seller at (512) 555-0142."
],
"schema": {
"name": "",
"price": "",
"date": ""
}
}' |
apify call scrapers_lat/text-to-json-tool --silent --output-dataset
```
## MCP server setup
```json
{
"mcpServers": {
"apify": {
"command": "npx",
"args": [
"mcp-remote",
"https://mcp.apify.com/?tools=scrapers_lat/text-to-json-tool",
"--header",
"Authorization: Bearer "
]
}
}
}
```
## OpenAPI specification
```json
{
"openapi": "3.0.1",
"info": {
"title": "Tool: Any Text to Structured JSON",
"description": "Convert any unstructured text into clean structured JSON that matches the schema you define, using premium AI. Paid Apify plans only.",
"version": "0.1",
"x-build-id": "ENbhcHh5RGNaludd3"
},
"servers": [
{
"url": "https://api.apify.com/v2"
}
],
"paths": {
"/acts/scrapers_lat~text-to-json-tool/run-sync-get-dataset-items": {
"post": {
"operationId": "run-sync-get-dataset-items-scrapers_lat-text-to-json-tool",
"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": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK"
}
}
}
},
"/acts/scrapers_lat~text-to-json-tool/runs": {
"post": {
"operationId": "runs-sync-scrapers_lat-text-to-json-tool",
"x-openai-isConsequential": false,
"summary": "Executes an Actor and returns information about the initiated run in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$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": {
"$ref": "#/components/schemas/runsResponseSchema"
}
}
}
}
}
}
},
"/acts/scrapers_lat~text-to-json-tool/run-sync": {
"post": {
"operationId": "run-sync-scrapers_lat-text-to-json-tool",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$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",
"required": [
"texts"
],
"properties": {
"texts": {
"title": "Texts to convert",
"type": "array",
"description": "A list of texts to turn into JSON. Each item is either a plain string or an object with a text field. Provide one item per record you want back."
},
"schema": {
"title": "Schema to extract",
"type": "object",
"description": "A JSON object describing the fields to extract. Keys are the field names you want, values are examples or empty strings. The tool returns one object per text matching these keys."
},
"maxItems": {
"title": "Max texts",
"minimum": 1,
"maximum": 100000,
"type": "integer",
"description": "Cap how many texts to convert this run. Optional."
}
}
},
"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
}
}
}
}
}
}
}
}
}
}
```