Pricing

from $0.00001 / actor start

Scribd Downloader

Download publicly accessible Scribd documents as PDF files with ease. Simply provide the document ID from any Scribd URL (e.g., scribd.com/document/528017616/...) and the Actor will automatically fetch and save the file. Automate document retrieval, bulk downloading workflows.

Pricing

from $0.00001 / actor start

Rating

0.0

(0)

Developer

apisupply

Actor stats

Bookmarked

Total users

Monthly active users

3 days ago

Last modified

Categories

Social media

Other

Integrations

You can access the Scribd Downloader programmatically from your own applications by using the Apify API. You can also choose the language preference from below. To use the Apify API, you’ll need an Apify account and your API token, found in API & Integrations in Apify Console.

Python

JavaScript

CLI

OpenAPI

HTTP

MCP

1from apify_client import ApifyClient
2
3# Initialize the ApifyClient with your Apify API token
4# Replace '<YOUR_API_TOKEN>' with your token.
5client = ApifyClient("<YOUR_API_TOKEN>")
6
7# Prepare the Actor input
8run_input = { "documentIds": ["424279284"] }
9
10# Run the Actor and wait for it to finish
11run = client.actor("apisupply/scribd-downloader").call(run_input=run_input)
12
13# Fetch and print Actor results from the run's dataset (if there are any)
14print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
15for item in client.dataset(run.default_dataset_id).iterate_items():
16    print(item)
17
18# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

Scribd Downloader API in Python

The Apify API client for Python is the official library that allows you to use Scribd Downloader API in Python, providing convenience functions and automatic retries on errors.

Install the apify-client

$pip install apify-client

Other API clients include:

Scribd Downloader API in JavaScript

Scribd Downloader API through CLI

Scribd Downloader OpenAPI definition

Scribd Downloader API

Scribd Scraper

jupri/scribd

💫 Search Scribd.com Documents

cat

153

Scribd Scraper - Low-cost💲🔥📄📚

delectable_incubator/scribd-scraper-low-cost

📚🔍 Extract public Scribd documents by keyword with ease. Collect document titles, authors, page counts, upload dates, descriptions, categories, thumbnails, and document URLs. Ideal for academic research, content discovery, document indexing, knowledge management, and research dataset creation 📊🚀

Prime Scrape

5.0

Scribd Document Search Scraper

solidcode/scribd-scraper

[💰 $3.5 / 1K] Search Scribd by keyword and export structured metadata for every matching document, book, audiobook, sheet music, or podcast — title, author, type, page count, ratings, views, language, categories, and links.

SolidCode

Scribd Document Search Scraper 🔍📄📚 - Cheap

scrapestorm/scribd-document-search-scraper---cheap

📚 Quickly extract public Scribd documents using any keyword — ideal for researchers, curators, and analysts 🔍 Just enter a search term to get structured data like title, author, page count & upload date. Perfect for building content libraries or powering research tools 📈

Storm_Scraper

5.0

Scribd Document Search Scraper 🔍📄📚 - Pay Per result

scrapestorm/scribd-document-search-scraper---pay-per-result

Storm_Scraper

Elite Document Ocr Lite

thepattyroller/elite-document-ocr-lite

Basic document text extraction and processing. Extract text from documents, analyze document structure, and extract structured data from invoices and receipts. Perfect for document automation workflows.

Logan Kiser

Document Reader & Verification

mina_safwat/document-reader

The actor reads info from the document and verify the authenticity

Mina

PDF to Text API | Document Extraction for LLMs & RAG

andok/pdf-text-converter

Convert bulk PDF documents via URL into clean, raw text. The perfect document scraper for LLMs, vector databases, and RAG pipelines.

Andok

PDF & Document to Markdown - PDF, DOCX & HTML for LLMs

entranced_gelato/ai-document-reader

Turn any PDF, DOCX, TXT, or HTML document into clean, LLM-ready text + Markdown with metadata (title, pages, word count) and an optional AI summary. The document counterpart to a web reader — built for RAG ingestion, document Q&A, and AI agents (LangChain, LlamaIndex). Fast, structured, single-call.