# Twitter / X Scraper Unlimited – Tweets, Profiles & Hashtags (`dev-sinior/twitter-scraper-unlimited`) Actor

Extract tweets, profiles, followers and hashtags from X.com (Twitter) with no volume limits. Search by keyword, date, language or user. Pay-per-event pricing. Exports to JSON & CSV.

- **URL**: https://apify.com/dev-sinior/twitter-scraper-unlimited.md
- **Developed by:** [DEV-SINIOR](https://apify.com/dev-sinior) (community)
- **Categories:** Social media, News, Videos
- **Stats:** 23 total users, 4 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $0.50 / 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.

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

# Actor input Schema

## `mode` (type: `string`):

What to scrape: search results, user profile, user tweets, or hashtag.

## `queries` (type: `array`):

Search: keywords. Profile/Tweets: usernames (without @). Hashtag: tags (without #).

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

Maximum tweets or profiles to collect per query.

## `language` (type: `string`):

Filter by language code (e.g. 'en', 'fr', 'es'). Leave empty for all.

## `fromDate` (type: `string`):

Only tweets after this date. Format: YYYY-MM-DD

## `toDate` (type: `string`):

Only tweets before this date. Format: YYYY-MM-DD

## `includeReplies` (type: `boolean`):

Include reply tweets in results.

## `includeRetweets` (type: `boolean`):

Include retweets in results.

## `proxyCountry` (type: `string`):

Country code for residential proxy (recommended: US).

## Actor input object example

```json
{
  "mode": "search",
  "queries": [
    "artificial intelligence",
    "web scraping 2026"
  ],
  "maxItems": 100,
  "language": "en",
  "fromDate": "2024-01-01",
  "toDate": "2024-12-31",
  "includeReplies": false,
  "includeRetweets": true,
  "proxyCountry": "US"
}
```

# Actor output Schema

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

tweet or profile

## `id` (type: `string`):

Tweet ID

## `text` (type: `string`):

Full tweet content

## `createdAt` (type: `string`):

Tweet creation timestamp (ISO)

## `lang` (type: `string`):

Tweet language code

## `likeCount` (type: `string`):

Number of likes

## `retweetCount` (type: `string`):

Number of retweets

## `replyCount` (type: `string`):

Number of replies

## `quoteCount` (type: `string`):

Number of quote tweets

## `bookmarkCount` (type: `string`):

Number of bookmarks

## `viewCount` (type: `string`):

Number of views/impressions

## `isRetweet` (type: `string`):

Whether tweet is a retweet

## `isQuote` (type: `string`):

Whether tweet is a quote tweet

## `isReply` (type: `string`):

Whether tweet is a reply

## `hasMedia` (type: `string`):

Whether tweet contains media

## `hashtags` (type: `string`):

Hashtags in the tweet

## `mentions` (type: `string`):

Mentioned usernames

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

Direct link on x.com

## `twitterUrl` (type: `string`):

Direct link on twitter.com

## `keyword` (type: `string`):

Search query that returned this

## `authorUsername` (type: `string`):

Author @username

## `authorName` (type: `string`):

Author display name

## `authorFollowers` (type: `string`):

Author follower count

## `authorVerified` (type: `string`):

Blue checkmark

## `authorImageUrl` (type: `string`):

Author profile image URL

# 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("dev-sinior/twitter-scraper-unlimited").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("dev-sinior/twitter-scraper-unlimited").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 '{}' |
apify call dev-sinior/twitter-scraper-unlimited --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "command": "npx",
            "args": [
                "mcp-remote",
                "https://mcp.apify.com/?tools=dev-sinior/twitter-scraper-unlimited",
                "--header",
                "Authorization: Bearer <YOUR_API_TOKEN>"
            ]
        }
    }
}

```

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/acts/hhe6fHJvLr6v4zOiJ/builds/aZ6MUSPs5RbRZTlbP/openapi.json