# Instagram Followers Exporter – JSON to CSV (`signal_lab/instagram-followers-exporter`) Actor

Convert your own Instagram Data Download follower JSON to clean CSV, Excel, or API rows. No Instagram login, session cookies, or scraping.

- **URL**: https://apify.com/signal\_lab/instagram-followers-exporter.md
- **Developed by:** [Signal Lab](https://apify.com/signal_lab) (community)
- **Categories:** Social media, Automation, Developer tools
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $0.50 / 1,000 instagram relationship rows

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

## Instagram Followers Exporter – JSON to CSV

Turn your own Instagram Data Download JSON into analysis-ready follower rows. This privacy-first converter does not log in to Instagram, use session cookies, or scrape another account.

### What you can do

- Convert Instagram follower exports to CSV, Excel, or JSON.
- Create a clean backup with usernames, profile links, and follow timestamps.
- Deduplicate nested export records for audience operations.
- Process inline JSON or your own signed HTTPS export URLs.

### Get the source file

In Meta Accounts Center, request a download of your Instagram information and choose JSON format. Select the followers/following information you are authorized to use. When the download is ready, locate the follower JSON file (commonly named `followers_1.json`). Meta may change the exact menu labels.

### Start quickly

Paste one or more export records into `followers`. The Actor recursively reads Instagram’s `string_list_data` structure.

```json
{
  "followers": [
    {
      "string_list_data": [
        {
          "href": "https://www.instagram.com/example/",
          "value": "example",
          "timestamp": 1700000000
        }
      ]
    }
  ],
  "maxItems": 10
}
```

For larger files, provide direct signed HTTPS JSON links in `exportUrls`. URLs must return JSON without an interactive login page. Use `maxItems` as a predictable hard cap.

### Output

Each paid result is one deduplicated relationship row with `username`, `profileUrl`, `followedAt`, `source`, and `scrapedAt`. Export the dataset as JSON, CSV, Excel, XML, or RSS, or consume it through the Apify API.

### Troubleshooting

- **No rows:** make sure the pasted object contains Instagram’s `string_list_data` records.
- **URL fails:** use an HTTPS link that directly returns the JSON file and has not expired.
- **Only part of the export appears:** increase `maxItems` and include every split follower file.
- **Need someone else’s live follower list:** this Actor intentionally does not scrape or bypass Instagram access controls.

### Free product guide

See the [Instagram Followers Exporter workflow, privacy model, and expected output](https://signal-lab-tools.vitaxastar.chatgpt.site/tools/instagram-followers-exporter), or browse [all Signal Lab data tools](https://signal-lab-tools.vitaxastar.chatgpt.site).

### Pricing and responsible use

Launch pricing is **$0.50 per 1,000 successful relationship rows** plus the small start event shown in the Pricing tab. You pay for rows actually produced. Use only exports you are authorized to process and protect personal data according to applicable law.

# Actor input Schema

## `followers` (type: `array`):

Paste the contents or records from followers\_1.json.

## `exportUrls` (type: `array`):

Optional HTTPS URLs pointing to your own follower JSON files.

## `maxItems` (type: `integer`):

Hard cap for emitted dataset rows and pay-per-event charges.

## Actor input object example

```json
{
  "followers": [
    {
      "string_list_data": [
        {
          "href": "https://www.instagram.com/example/",
          "value": "example",
          "timestamp": 1700000000
        }
      ]
    }
  ],
  "exportUrls": [],
  "maxItems": 10
}
```

# Actor output Schema

## `results` (type: `string`):

No description

## `summary` (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 '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "followers": [
        {
            "string_list_data": [
                {
                    "href": "https://www.instagram.com/example/",
                    "value": "example",
                    "timestamp": 1700000000
                }
            ]
        }
    ],
    "maxItems": 10
};

// Run the Actor and wait for it to finish
const run = await client.actor("signal_lab/instagram-followers-exporter").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 = {
    "followers": [{ "string_list_data": [{
                    "href": "https://www.instagram.com/example/",
                    "value": "example",
                    "timestamp": 1700000000,
                }] }],
    "maxItems": 10,
}

# Run the Actor and wait for it to finish
run = client.actor("signal_lab/instagram-followers-exporter").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 '{
  "followers": [
    {
      "string_list_data": [
        {
          "href": "https://www.instagram.com/example/",
          "value": "example",
          "timestamp": 1700000000
        }
      ]
    }
  ],
  "maxItems": 10
}' |
apify call signal_lab/instagram-followers-exporter --silent --output-dataset

```

## MCP server setup

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

```

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/5b8zsKVnfEdu3RhEc/builds/kWFgYlvmaximF1Wir/openapi.json