# Excel to JSON Converter — XLSX/XLS Spreadsheet, All Sheets API (`eliai/excel-to-json`) Actor

Convert Excel to JSON via API. Input: a URL to an .xlsx or .xls spreadsheet file. Output: JSON with every sheet as an array of row objects, headers detected automatically. Handles multi-sheet workbooks. Flat, cheap pay-per-file pricing — one charge per converted spreadsheet.

- **URL**: https://apify.com/eliai/excel-to-json.md
- **Developed by:** [Anthony Snider](https://apify.com/eliai) (community)
- **Categories:** Developer tools, Automation
- **Stats:** 2 total users, 2 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

$30.00 / 1,000 file conversions

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.

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

## 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

## Excel (XLSX) to JSON Converter

Turn any Excel workbook URL into clean, structured JSON — every sheet as an array of row objects, headers detected automatically.

**Live on the Apify Store — run it instantly or call it as an agent tool via Apify MCP.**

### What you get

- Point it at any `.xlsx` / `.xls` file URL and get back parsed JSON.
- Every sheet converted to an array of row objects keyed by the detected header row.
- `sheetNames`, per-sheet `columns`, `rowCount`, and `rows`.
- Pick a single sheet by name or index, cap rows, or convert in bulk.

### Input

```json
{
  "url": "https://github.com/SheetJS/test_files/raw/master/AutoFilter.xlsx",
  "sheet": "Sheet1",
  "maxRows": 1000
}
```

- `url` — direct URL to the Excel workbook (required).
- `urls` — optional array of extra workbook URLs (up to 25 total per run).
- `sheet` — optional sheet name or 0-based index; omit to convert every sheet.
- `maxRows` — optional cap on data rows per sheet (default 5000).

### Output

```json
{
  "url": "https://github.com/SheetJS/test_files/raw/master/AutoFilter.xlsx",
  "finalUrl": "https://raw.githubusercontent.com/SheetJS/test_files/master/AutoFilter.xlsx",
  "status": 200,
  "sheetNames": ["Sheet1"],
  "sheets": {
    "Sheet1": {
      "rowCount": 3,
      "columns": ["Column1", "Column2"],
      "rows": [
        { "Column1": "a", "Column2": 1 },
        { "Column1": "b", "Column2": 2 }
      ]
    }
  }
}
```

Each input produces one dataset item. Failed inputs return `{ url, error }` so one bad file never breaks the run.

# Actor input Schema

## `url` (type: `string`):

Direct URL to an .xlsx or .xls workbook to convert.

## `urls` (type: `array`):

Optional list of additional Excel file URLs to convert in one run (max 25 total).

## `sheet` (type: `string`):

Convert only this sheet. Accepts a sheet name or a 0-based index. Leave empty to convert all sheets.

## `maxRows` (type: `integer`):

Cap the number of data rows returned per sheet (header row excluded).

## Actor input object example

```json
{
  "url": "https://graveyard.broke2builtai.com/assets/sample.xlsx",
  "maxRows": 5000
}
```

# 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 = {
    "url": "https://graveyard.broke2builtai.com/assets/sample.xlsx"
};

// Run the Actor and wait for it to finish
const run = await client.actor("eliai/excel-to-json").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 = { "url": "https://graveyard.broke2builtai.com/assets/sample.xlsx" }

# Run the Actor and wait for it to finish
run = client.actor("eliai/excel-to-json").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 '{
  "url": "https://graveyard.broke2builtai.com/assets/sample.xlsx"
}' |
apify call eliai/excel-to-json --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "command": "npx",
            "args": [
                "mcp-remote",
                "https://mcp.apify.com/?tools=eliai/excel-to-json",
                "--header",
                "Authorization: Bearer <YOUR_API_TOKEN>"
            ]
        }
    }
}

```

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/k87yVZ5r4Vq9NA68b/builds/nzaJCl8Ve37CbUcxt/openapi.json