# CSV to JSON Converter - Convert CSV by URL or Text API (`eliai/csv-to-json`) Actor

Convert CSV to JSON via API - from a file URL or pasted raw text (fields: url or csv). Auto-detects delimiter (comma, tab, semicolon, pipe), types values (numbers, booleans, dates), handles quoted fields. Returns JSON records + column/type report. Sync run for agents and pipelines. $0.02 per file.

- **URL**: https://apify.com/eliai/csv-to-json.md
- **Developed by:** [Anthony Snider](https://apify.com/eliai) (community)
- **Categories:** Developer tools, Automation
- **Stats:** 1 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

$20.00 / 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

## CSV to JSON Converter

Convert CSV to JSON in one call: give it a CSV file URL or paste raw CSV text, and get back a clean JSON array of typed records — delimiter auto-detected, numbers/booleans/dates typed, quoted fields handled correctly.

Use it from the web UI, call it as a plain HTTP API (sync run-and-return: one request in, JSON out), or wire it into an agent as an Apify MCP tool.

### Common use cases

- **Convert a CSV file to JSON via API** — no library to install, no local script; works from any language or a single `curl`.
- **Parse a CSV export into JSON records** — Google Sheets / Excel "save as CSV", Shopify, Stripe, or analytics exports, straight into a pipeline.
- **Feed spreadsheet data to an LLM or agent** — agents get typed JSON rows plus a column/type report instead of raw CSV text.
- **Normalize messy CSVs** — semicolon-, tab-, or pipe-delimited files and quoted fields with embedded commas or newlines parse correctly.
- **Preview a dataset's schema** — get the column list and inferred type per column before ingesting.

### Features

- **Auto delimiter detection** — comma, tab, semicolon, or pipe; no config needed.
- **Type inference** — numbers, booleans, and dates are typed automatically (everything else stays a string).
- **Quoted fields handled** — embedded commas, newlines, and quotes parse correctly.
- **URL or raw text** — fetch a remote CSV (`url`) or paste it inline (`csv`).
- **Column + type report** — the column list and inferred type per column come back alongside the rows.

### Input

Fetch a CSV by URL:

```json
{
  "url": "https://raw.githubusercontent.com/datablist/sample-csv-files/main/files/organizations/organizations-100.csv",
  "header": true,
  "maxRows": 50000
}
```

Or paste raw CSV text instead (field name is `csv`):

```json
{
  "csv": "name,age,active\nAda,36,true\nGrace,42,false",
  "delimiter": ""
}
```

If both `url` and `csv` are given, the URL wins. Leave `delimiter` empty to auto-detect. Set `header: false` to get generated column names (`column_1`, `column_2`, …).

### Output

One result object in the dataset:

```json
{
  "source": "inline-csv",
  "rowCount": 2,
  "columns": ["name", "age", "active"],
  "types": { "name": "string", "age": "number", "active": "boolean" },
  "delimiter": ",",
  "rows": [
    { "name": "Ada", "age": 36, "active": true },
    { "name": "Grace", "age": 42, "active": false }
  ]
}
```

On a bad input (unreachable URL, empty CSV) you get `{ "source": ..., "error": "..." }` instead — no charge for failed conversions.

### Call it as an API

```bash
curl -X POST "https://api.apify.com/v2/acts/eliai~csv-to-json/run-sync-get-dataset-items?token=YOUR_APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"csv": "name,age\nAda,36"}'
```

The response body is the JSON result shown above — no polling needed.

### Pricing and limits

- **$0.02 per file converted** (pay-per-event; you only pay for successful conversions).
- `maxRows` defaults to 50,000 data rows; hard cap 200,000.
- The `url` must be a direct link to a CSV file (not an HTML page around it).

# Actor input Schema

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

A direct URL to a CSV file to fetch and convert.

## `csv` (type: `string`):

Paste raw CSV text instead of a URL. If both are given, the URL is used.

## `delimiter` (type: `string`):

Field delimiter. Leave empty to auto-detect (comma, tab, semicolon, pipe).

## `header` (type: `boolean`):

Treat the first row as column names. If off, columns are named column\_1, column\_2, ...

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

Maximum number of data rows to include in the output.

## Actor input object example

```json
{
  "url": "https://raw.githubusercontent.com/datablist/sample-csv-files/main/files/organizations/organizations-100.csv",
  "header": true,
  "maxRows": 50000
}
```

# 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://raw.githubusercontent.com/datablist/sample-csv-files/main/files/organizations/organizations-100.csv"
};

// Run the Actor and wait for it to finish
const run = await client.actor("eliai/csv-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://raw.githubusercontent.com/datablist/sample-csv-files/main/files/organizations/organizations-100.csv" }

# Run the Actor and wait for it to finish
run = client.actor("eliai/csv-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://raw.githubusercontent.com/datablist/sample-csv-files/main/files/organizations/organizations-100.csv"
}' |
apify call eliai/csv-to-json --silent --output-dataset

```

## MCP server setup

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

```

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/7GVW9O4m2OHoAdOn2/builds/cG3E5LF8TdZhhMfmN/openapi.json