# My Actor (`engaged_thenardite/my-actor`) Actor

nahhhh!

- **URL**: https://apify.com/engaged\_thenardite/my-actor.md
- **Developed by:** [Victor James](https://apify.com/engaged_thenardite) (community)
- **Categories:** Automation
- **Stats:** 2 total users, 0 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

Pay per usage

This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have.

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

## 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

## X / Twitter Auto Messenger Actor

This Apify Actor automatically sends personalized direct messages (DMs) on X/Twitter. It reads a list of target usernames and messages from a Google Sheet and sends the DMs using the Playwright/Chromium browser.

### Features

- **Google Sheet Integration:** Reads usernames and messages directly from a Google Sheet.
- **Automated DM Sending:** Uses a browser to navigate X and send messages simulating human behavior.
- **Status Reporting:** Automatically updates the Google Sheet with the status of each message (e.g., "Sent", "User not found", etc.).
- **Authentication:** Supports using raw cookie strings or specific `auth_token`/`ct0` cookies for login.

### How it works

1. The Actor reads the configured Google Sheet for rows containing a username (Column A) and a custom message (Column B).
2. It logs into X using the provided cookies.
3. For each username, it navigates to their profile and opens the DM window.
4. It types the personalized message and sends it.
5. It then writes back the status to the Google Sheet (Column C) using your Google Apps Script Web App URL and pushes the result to the Apify dataset.

### Input Configuration

- **Google Sheet URL:** The URL of the Google Sheet containing usernames and messages.
- **X.com Cookie String (or auth\_token/ct0):** Your authentication cookies to log into X.
- **Messages Per Run:** Maximum number of messages to send per execution (default: 20).
- **Base Delay:** Wait time between messages to avoid rate limits.
- **Google Apps Script Web App URL:** The URL of the deployed Apps Script that allows the Actor to write the status back to the sheet.

### Output

The Actor stores its results in the default Apify Dataset. Each record includes:

- username: The target X username.
- message: The message that was sent.
- status: The result of the operation (e.g., "Sent" or an error message).
- imestamp: When the message was processed.

# Actor input Schema

## `sheetUrl` (type: `string`):

URL of the Google Sheet containing usernames (Column A) and messages (Column B).

## `cookieString` (type: `string`):

Raw cookie string for authentication (optional if auth\_token/ct0 are provided).

## `auth_token` (type: `string`):

Value of the auth\_token cookie.

## `ct0` (type: `string`):

Value of the ct0 cookie.

## `messagesPerRun` (type: `integer`):

Maximum number of messages to send in a single execution.

## `delaySeconds` (type: `integer`):

Base delay between sending messages (will be randomized +/- 5 seconds).

## `pinCode` (type: `string`):

Optional PIN code if X requires it for DM recovery.

## `sheetWebAppUrl` (type: `string`):

The deployed Web App URL from your Google Sheet Apps Script (required for writing status to Column C).

## Actor input object example

```json
{
  "messagesPerRun": 20,
  "delaySeconds": 12
}
```

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

// Prepare Actor input
const input = {};

// Run the Actor and wait for it to finish
const run = await client.actor("engaged_thenardite/my-actor").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 = {}

# Run the Actor and wait for it to finish
run = client.actor("engaged_thenardite/my-actor").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 '{}' |
apify call engaged_thenardite/my-actor --silent --output-dataset

```

## MCP server setup

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

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/8HPfY3MFnmKy0GiNx/builds/kN1pnPjFqij8JofiF/openapi.json