# Twitter Timeline Scraper (`powerai/twitter-timeline-scraper`) Actor
Extract tweets from any public Twitter user's timeline with full metadata, supporting auto-pagination and custom result limits.
- **URL**: https://apify.com/powerai/twitter-timeline-scraper.md
- **Developed by:** [PowerAI](https://apify.com/powerai) (community)
- **Categories:** Social media
- **Stats:** 115 total users, 6 monthly users, 98.9% runs succeeded, 3 bookmarks
- **User rating**: No ratings yet
## Pricing
from $4.99 / 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 a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases.
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.
In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md):
```bash
npm install apify-client
```
In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md):
```bash
pip install apify-client
```
In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md):
````bash
# MacOS / Linux
curl -fsSL https://apify.com/install-cli.sh | bash
# Windows
irm https://apify.com/install-cli.ps1 | iex
```bash
In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md).
If your project is in a different language, use 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
## 🐦 Twitter Timeline Scraper
Extract the latest tweets from any public Twitter user's timeline with detailed metadata.
This actor leverages the Twitter API to fetch tweets, including tweet content, engagement metrics, media, and author information.
### Features
- Fetches tweets from a specified user's timeline.
- Supports pagination and automatic fetching up to the specified `maxResults`.
- Returns rich metadata for each tweet, including media, engagement, and author details.
### Input
| Field | Type | Description |
|-------------|---------|--------------------------------------------------|
| screenname | string | Twitter username (without @) |
| maxResults | integer | Maximum number of tweets to fetch |
### Output
An array of tweet objects, each with the following structure (see below for details):
- `tweet_id`
- `created_at`
- `text`
- `favorites`
- `retweets`
- `replies`
- `quotes`
- `views`
- `lang`
- `source`
- `media` (photos/videos)
- `author` (user info)
- ...and more
### Example Output
```json
[
{
"tweet_id": "1927977858812760412",
"bookmarks": 832,
"created_at": "Thu May 29 06:38:36 +0000 2025",
"favorites": 24255,
"text": "https://t.co/CSwbjnzNao",
"lang": "zxx",
"source": "Twitter for iPhone",
"views": "1781258",
"quotes": 224,
"entities": {
"hashtags": [],
"symbols": [],
"timestamps": [],
"urls": [],
"user_mentions": []
},
"replies": 2367,
"retweets": 3061,
"conversation_id": "1927977858812760412",
"media": {
"video": [
{
"media_url_https": "https://pbs.twimg.com/ext_tw_video_thumb/1796190801073950721/pu/img/GFLwceK_ddA8a1sJ.jpg",
"variants": [
{
"content_type": "application/x-mpegURL",
"url": "https://video.twimg.com/ext_tw_video/1796190801073950721/pu/pl/7lnLBQyUTTdiGa4e.m3u8?tag=14&v=cfc"
},
{
"bitrate": 256000,
"content_type": "video/mp4",
"url": "https://video.twimg.com/ext_tw_video/1796190801073950721/pu/vid/avc1/480x270/J4lj36p61IfeGFKK.mp4?tag=14"
},
{
"bitrate": 832000,
"content_type": "video/mp4",
"url": "https://video.twimg.com/ext_tw_video/1796190801073950721/pu/vid/avc1/640x360/aZEEXCafUCsVQ_8U.mp4?tag=14"
},
{
"bitrate": 2176000,
"content_type": "video/mp4",
"url": "https://video.twimg.com/ext_tw_video/1796190801073950721/pu/vid/avc1/1280x720/Zn-lTHriGHWKYv8K.mp4?tag=14"
},
{
"bitrate": 10368000,
"content_type": "video/mp4",
"url": "https://video.twimg.com/ext_tw_video/1796190801073950721/pu/vid/avc1/1920x1080/ijSv3sREG6z6qN5h.mp4?tag=14"
}
],
"aspect_ratio": [
16,
9
],
"duration": 41770,
"original_info": {
"height": 1080,
"width": 1920,
"focus_rects": []
},
"id": "1796190801073950721"
}
]
},
"author": {
"rest_id": "44196397",
"name": "Elon Musk",
"screen_name": "elonmusk",
"avatar": "https://pbs.twimg.com/profile_images/1926284313365979137/o2cF3MeJ_normal.jpg",
"blue_verified": true
},
"scrapedAt": "2025-05-29T09:02:38.547Z"
},
...
]
````
### Notes
- Only public timelines are supported.
- The actor will automatically paginate until `maxResults` is reached or no more tweets are available.
# Actor input Schema
## `screenname` (type: `string`):
The Twitter username (without @) whose timeline you want to scrape.
## `maxResults` (type: `integer`):
Maximum number of tweets to fetch.
## Actor input object example
```json
{
"screenname": "elonmusk",
"maxResults": 20
}
```
# 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 '' with your token
const client = new ApifyClient({
token: '',
});
// Prepare Actor input
const input = {};
// Run the Actor and wait for it to finish
const run = await client.actor("powerai/twitter-timeline-scraper").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 '' with your token.
client = ApifyClient("")
# Prepare the Actor input
run_input = {}
# Run the Actor and wait for it to finish
run = client.actor("powerai/twitter-timeline-scraper").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 powerai/twitter-timeline-scraper --silent --output-dataset
```
## MCP server setup
```json
{
"mcpServers": {
"apify": {
"command": "npx",
"args": [
"mcp-remote",
"https://mcp.apify.com/?tools=powerai/twitter-timeline-scraper",
"--header",
"Authorization: Bearer "
]
}
}
}
```
## OpenAPI specification
```json
{
"openapi": "3.0.1",
"info": {
"title": "Twitter Timeline Scraper",
"description": "Extract tweets from any public Twitter user's timeline with full metadata, supporting auto-pagination and custom result limits.",
"version": "0.0",
"x-build-id": "aqDoJA6hqfN1jlRPQ"
},
"servers": [
{
"url": "https://api.apify.com/v2"
}
],
"paths": {
"/acts/powerai~twitter-timeline-scraper/run-sync-get-dataset-items": {
"post": {
"operationId": "run-sync-get-dataset-items-powerai-twitter-timeline-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK"
}
}
}
},
"/acts/powerai~twitter-timeline-scraper/runs": {
"post": {
"operationId": "runs-sync-powerai-twitter-timeline-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor and returns information about the initiated run in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK",
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/runsResponseSchema"
}
}
}
}
}
}
},
"/acts/powerai~twitter-timeline-scraper/run-sync": {
"post": {
"operationId": "run-sync-powerai-twitter-timeline-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK"
}
}
}
}
},
"components": {
"schemas": {
"inputSchema": {
"type": "object",
"required": [
"screenname",
"maxResults"
],
"properties": {
"screenname": {
"title": "Twitter Username",
"type": "string",
"description": "The Twitter username (without @) whose timeline you want to scrape.",
"default": "elonmusk"
},
"maxResults": {
"title": "Max Results",
"minimum": 20,
"maximum": 50000,
"type": "integer",
"description": "Maximum number of tweets to fetch.",
"default": 20
}
}
},
"runsResponseSchema": {
"type": "object",
"properties": {
"data": {
"type": "object",
"properties": {
"id": {
"type": "string"
},
"actId": {
"type": "string"
},
"userId": {
"type": "string"
},
"startedAt": {
"type": "string",
"format": "date-time",
"example": "2025-01-08T00:00:00.000Z"
},
"finishedAt": {
"type": "string",
"format": "date-time",
"example": "2025-01-08T00:00:00.000Z"
},
"status": {
"type": "string",
"example": "READY"
},
"meta": {
"type": "object",
"properties": {
"origin": {
"type": "string",
"example": "API"
},
"userAgent": {
"type": "string"
}
}
},
"stats": {
"type": "object",
"properties": {
"inputBodyLen": {
"type": "integer",
"example": 2000
},
"rebootCount": {
"type": "integer",
"example": 0
},
"restartCount": {
"type": "integer",
"example": 0
},
"resurrectCount": {
"type": "integer",
"example": 0
},
"computeUnits": {
"type": "integer",
"example": 0
}
}
},
"options": {
"type": "object",
"properties": {
"build": {
"type": "string",
"example": "latest"
},
"timeoutSecs": {
"type": "integer",
"example": 300
},
"memoryMbytes": {
"type": "integer",
"example": 1024
},
"diskMbytes": {
"type": "integer",
"example": 2048
}
}
},
"buildId": {
"type": "string"
},
"defaultKeyValueStoreId": {
"type": "string"
},
"defaultDatasetId": {
"type": "string"
},
"defaultRequestQueueId": {
"type": "string"
},
"buildNumber": {
"type": "string",
"example": "1.0.0"
},
"containerUrl": {
"type": "string"
},
"usage": {
"type": "object",
"properties": {
"ACTOR_COMPUTE_UNITS": {
"type": "integer",
"example": 0
},
"DATASET_READS": {
"type": "integer",
"example": 0
},
"DATASET_WRITES": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_READS": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_WRITES": {
"type": "integer",
"example": 1
},
"KEY_VALUE_STORE_LISTS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_READS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_WRITES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_INTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_EXTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_SERPS": {
"type": "integer",
"example": 0
}
}
},
"usageTotalUsd": {
"type": "number",
"example": 0.00005
},
"usageUsd": {
"type": "object",
"properties": {
"ACTOR_COMPUTE_UNITS": {
"type": "integer",
"example": 0
},
"DATASET_READS": {
"type": "integer",
"example": 0
},
"DATASET_WRITES": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_READS": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_WRITES": {
"type": "number",
"example": 0.00005
},
"KEY_VALUE_STORE_LISTS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_READS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_WRITES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_INTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_EXTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_SERPS": {
"type": "integer",
"example": 0
}
}
}
}
}
}
}
}
}
}
```