# Telegram Posts Scraper - Low-cost 💲🔥📲📢 (`delectable_incubator/telegram-posts-scraper-low-cost`) Actor
📲 Extract public Telegram channel posts at scale. Collect post text, media, views, reactions, timestamps, post URLs, attachments, & engagement metrics in a structured format. Ideal for OSINT, crypto monitoring, social media analytics, influencer research, trend tracking & intelligence gathering 📊
- **URL**: https://apify.com/delectable\_incubator/telegram-posts-scraper-low-cost.md
- **Developed by:** [Prime Scrape](https://apify.com/delectable_incubator) (community)
- **Categories:** Automation, Social media, News
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet
## Pricing
from $0.00005 / actor start
This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage.
Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have.
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
---
## 📲📢 Telegram Channel Posts Scraper | Bulk Telegram Channels Scraper | Apify Actor
### 🚀 Extract Telegram Channel Posts in Seconds (No Code)
The **Telegram Channel Posts Scraper** is a powerful, scalable and SEO-optimized Apify Actor built to scrape **public Telegram channel posts** in bulk.
Extract posts, views, reactions, media, authors, timestamps, engagement metrics, and content data for social media intelligence, OSINT investigations, crypto monitoring, influencer tracking, AI datasets, and sentiment analysis.
---
## 🔥 Why This Telegram Scraper?
✔ Best Telegram channel scraper on Apify
✔ Bulk channel scraping (multiple channels at once)
✔ Fast & scalable extraction engine
✔ Public Telegram channel support
✔ 100% structured JSON / CSV / Excel output
✔ Ideal for OSINT & social media intelligence
✔ Perfect for researchers, analysts & agencies
✔ No coding required
---
## 🎯 What This Scraper Does
This Apify Actor extracts real-time posts directly from public Telegram channels.
Simply provide one or multiple Telegram channels and the scraper automatically collects posts and engagement metrics.
#### 📌 Core Features
✅ Scrape Telegram channel posts
✅ Bulk channel scraping (SEO BOOST 🚀)
✅ Multiple channels support
✅ Extract post content
✅ Extract views & reactions
✅ Extract media attachments
✅ Extract authors & timestamps
✅ Export clean structured datasets
✅ High-speed cloud extraction
---
## ⚡ Input Configuration (Simple & Powerful)
### 🔥 BULK CHANNEL MODE (SEO BOOST 🚀)
````
{
"channels": \[
"@durov",
"crypto\_news",
"fashion",
"https://t.me/crypto\_news",
"https://t.me/s/telegram"
],
"MAX\_ITEMS\_PER\_CHANNEL": 200
}
```
---
## 📊 Extracted Telegram Data (Structured Output)
| Field | Description |
|---------|-------------|
| channel | Channel username |
| postNumber | Telegram post ID |
| position | Position in extraction sequence |
| author | Post author |
| text | Full post content |
| datetime | Publication date |
| serviceDate | Display date |
| views | Number of views |
| url | Direct post URL |
| media | Attached media |
| reactions | Emoji reactions |
| scrapeTimestamp | Extraction timestamp |
---
## 💡 Use Cases (High Demand SEO Keywords)
Perfect for:
📲 Telegram scraping
🕵️ OSINT investigations
🪙 Crypto community monitoring
📊 Social media intelligence
📈 Influencer tracking
💬 Sentiment analysis
📰 News monitoring
🤖 AI training datasets
📚 Content archiving
⚡ Bulk Telegram extraction
---
## 🚀 Key Features (Apify SEO Optimized)
⚡ Bulk channel scraping support
🌍 Global Telegram coverage
📌 Engagement metrics extraction
🧠 Clean structured output
📊 High-speed extraction engine
🔁 Auto retry & stability system
💾 Export-ready datasets
⚙️ Scalable cloud execution
🚀 Enterprise-ready architecture
---
## 📤 Output Formats Supported
✔ JSON
✔ CSV
✔ Excel XLSX
✔ XML
✔ HTML
---
## 📦 Example Output
```
{
"channel": "durov",
"postNumber": 1234,
"position": 1,
"author": "Pavel Durov",
"text": "Telegram keeps growing 🚀",
"datetime": "2026-02-15T18:42:00.000Z",
"serviceDate": "Feb 15, 2026",
"views": "125430",
"url": "https://t.me/durov/1234",
"media": \[
{
"type": "image",
"url": "https://..."
}
],
"reactions": \[
{
"emoji": "🔥",
"count": 3200
}
],
"scrapeTimestamp": "2026-02-16T09:12:33.000Z"
}
````
---
## 📊 Preconfigured Dataset Views
#### 🔹 Overview
Includes:
- Channel
- Post Number
- Position
- Author
- Post Text
- Date & Time
- Views
- Reactions
- Media
- Post URL
Perfect for quick channel analysis.
---
#### 🔹 Detailed
Includes:
- Complete post metadata
- Media attachments
- Engagement metrics
- Reaction details
- Author information
- Full content
Ideal for:
📊 Social media intelligence
🕵️ OSINT investigations
📈 Engagement analysis
💬 Sentiment analysis
🤖 AI dataset creation
---
#### 🔹 By Channel
Compare multiple Telegram channels.
Includes:
- Channel Name
- Post ID
- Author
- Views
- Reactions
- Date
- URL
Perfect for comparing:
📲 Communities
🪙 Crypto channels
📰 News channels
📈 Influencers
---
## 🔥 Why This is the BEST Telegram Scraper on Apify?
✔ Optimized for Apify search ranking
✔ Bulk channel support (rare feature)
✔ High-performance extraction engine
✔ Rich engagement metrics
✔ Enterprise-ready scalability
✔ Clean structured datasets
✔ OSINT & social intelligence ready
✔ Perfect for SEO traffic & marketplace visibility
---
## 💸 Pricing
This scraper uses a **pay-per-result** pricing model.
💳 **Price: $0.49 / 1,000 results**
You only pay for successfully extracted records.
---
## ❓ FAQ (SEO BOOST SECTION)
#### Can I scrape multiple Telegram channels?
Yes — Bulk Channel Mode is fully supported.
#### Can I use channel URLs?
Yes.
#### Can I use channel usernames?
Yes.
#### Does the scraper collect reactions?
Yes.
#### Does the scraper collect views?
Yes.
#### Can I limit the number of posts?
Yes. Simply configure **MAX_ITEMS_PER_CHANNEL**.
#### Is coding required?
No — this is a 100% no-code Apify Actor.
#### Can I export the data?
Yes — JSON, CSV, Excel, XML and HTML are supported.
---
## ⚠️ Disclaimer
This tool is an independent data extraction solution and is **not affiliated with, endorsed by, or sponsored by Telegram.**
---
## 🔗 Related Actors
We are building the complete **PrimeScrape Social Media Intelligence Suite**.
👉 Coming Soon 🚀
---
## 🌍 PrimeScrape Ecosystem
Built for large-scale scraping, automation, AI datasets and market intelligence.
📲 Social media intelligence
🕵️ OSINT research
📊 Market analytics
📰 Content monitoring
🤖 AI training datasets
⚙️ Automation pipelines
📈 Community intelligence
---
## 📬 Support
⭐⭐⭐⭐⭐ Leave a review if you enjoy this actor.
📩 Contact us for custom scraping solutions, enterprise features or private actors.
# Actor input Schema
## `channels` (type: `array`):
List of Telegram channel usernames or URLs to scrape. You can use: @channelname, channelname, https://t.me/channelname, or https://t.me/s/channelname
## `MAX_ITEMS_PER_CHANNEL` (type: `integer`):
Maximum number of posts to extract per channel
## Actor input object example
```json
{
"channels": [
"crypto_news",
"durov"
],
"MAX_ITEMS_PER_CHANNEL": 50
}
````
# Actor output Schema
## `overview` (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 '' with your token
const client = new ApifyClient({
token: '',
});
// Prepare Actor input
const input = {
"channels": [
"crypto_news",
"durov"
],
"MAX_ITEMS_PER_CHANNEL": 50
};
// Run the Actor and wait for it to finish
const run = await client.actor("delectable_incubator/telegram-posts-scraper-low-cost").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 = {
"channels": [
"crypto_news",
"durov",
],
"MAX_ITEMS_PER_CHANNEL": 50,
}
# Run the Actor and wait for it to finish
run = client.actor("delectable_incubator/telegram-posts-scraper-low-cost").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 '{
"channels": [
"crypto_news",
"durov"
],
"MAX_ITEMS_PER_CHANNEL": 50
}' |
apify call delectable_incubator/telegram-posts-scraper-low-cost --silent --output-dataset
```
## MCP server setup
```json
{
"mcpServers": {
"apify": {
"command": "npx",
"args": [
"mcp-remote",
"https://mcp.apify.com/?tools=delectable_incubator/telegram-posts-scraper-low-cost",
"--header",
"Authorization: Bearer "
]
}
}
}
```
## OpenAPI specification
```json
{
"openapi": "3.0.1",
"info": {
"title": "Telegram Posts Scraper - Low-cost 💲🔥📲📢",
"description": "📲 Extract public Telegram channel posts at scale. Collect post text, media, views, reactions, timestamps, post URLs, attachments, & engagement metrics in a structured format. Ideal for OSINT, crypto monitoring, social media analytics, influencer research, trend tracking & intelligence gathering 📊",
"version": "0.0",
"x-build-id": "mnTMYS4hpIRgLcy9V"
},
"servers": [
{
"url": "https://api.apify.com/v2"
}
],
"paths": {
"/acts/delectable_incubator~telegram-posts-scraper-low-cost/run-sync-get-dataset-items": {
"post": {
"operationId": "run-sync-get-dataset-items-delectable_incubator-telegram-posts-scraper-low-cost",
"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": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK"
}
}
}
},
"/acts/delectable_incubator~telegram-posts-scraper-low-cost/runs": {
"post": {
"operationId": "runs-sync-delectable_incubator-telegram-posts-scraper-low-cost",
"x-openai-isConsequential": false,
"summary": "Executes an Actor and returns information about the initiated run in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$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": {
"$ref": "#/components/schemas/runsResponseSchema"
}
}
}
}
}
}
},
"/acts/delectable_incubator~telegram-posts-scraper-low-cost/run-sync": {
"post": {
"operationId": "run-sync-delectable_incubator-telegram-posts-scraper-low-cost",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$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": [
"channels",
"MAX_ITEMS_PER_CHANNEL"
],
"properties": {
"channels": {
"title": "Telegram Channels",
"type": "array",
"description": "List of Telegram channel usernames or URLs to scrape. You can use: @channelname, channelname, https://t.me/channelname, or https://t.me/s/channelname",
"items": {
"type": "string"
},
"default": [
"crypto_news",
"durov"
]
},
"MAX_ITEMS_PER_CHANNEL": {
"title": "Max Posts Per Channel",
"type": "integer",
"description": "Maximum number of posts to extract per channel",
"default": 50
}
}
},
"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
}
}
}
}
}
}
}
}
}
}
```