You can access the PDF to Markdown & JSON for LLMs/RAG 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

1import { ApifyClient } from 'apify-client';
2
3// Initialize the ApifyClient with your Apify API token
4// Replace the '<YOUR_API_TOKEN>' with your token
5const client = new ApifyClient({
6    token: '<YOUR_API_TOKEN>',
7});
8
9// Prepare Actor input
10const input = {
11    "pdfUrl": "https://arxiv.org/pdf/1706.03762"
12};
13
14// Run the Actor and wait for it to finish
15const run = await client.actor("wmora/pdf-to-markdown").call(input);
16
17// Fetch and print Actor results from the run's dataset (if any)
18console.log('Results from dataset');
19console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
20const { items } = await client.dataset(run.defaultDatasetId).listItems();
21items.forEach((item) => {
22    console.dir(item);
23});
24
25// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

PDF to Markdown & JSON for LLMs/RAG API in JavaScript

The Apify API client for JavaScript is the official library that allows you to use PDF to Markdown & JSON for LLMs/RAG API in JavaScript or TypeScript, providing convenience functions and automatic retries on errors.

Install the apify-client

$npm install apify-client

Other API clients include:

PDF to Markdown & JSON for LLMs/RAG API in Python

PDF to Markdown & JSON for LLMs/RAG API through CLI

PDF to Markdown & JSON for LLMs/RAG OpenAPI definition

PDF to Markdown & JSON for LLMs/RAG API

PDF to Markdown for RAG & LLMs — Tables

vivid_astronaut/pdf-to-markdown-for-rag

Convert PDFs into structured Markdown for RAG and LLM ingestion while preserving tables, headings, and reading order. No external parsing API key; tiered per-page pricing.

BRAINIALL Team

PDF to Markdown & JSON (RAG-Ready)

basisweb/pdf-to-markdown-rag

Convert PDFs to clean Markdown and structured JSON (text + tables) for RAG, LLMs, and vector DBs. Batch URLs, pay per page.

BasisWeb

PDF to Markdown for RAG

bindler/pdf-to-markdown

Convert PDFs to clean markdown with real reading order. Handles two-column layouts, detects headings and paragraphs. Built for RAG pipelines and LLM ingestion.

Neil Sangwaiya

PDF Extractor: PDF → Clean Markdown + JSON for LLM/RAG

boxbox10/pdf-extractor

Turn any PDF URL into clean, LLM-ready Markdown + structured JSON (title, metadata, per-page text, page count, word count, token count). Perfect for RAG pipelines, AI agents, and LLM document ingestion.

Marvin Eguilos

PDF Text Extractor - Markdown, Tables & RAG Chunks

readable_slash/pdf-text-extractor-structured

Extract text from PDF to clean Markdown with real tables, headings and lists. Bulk PDF to text conversion for RAG, LLM and vector database ingestion, with optional context-aware chunking. Detects scanned PDFs, handles encrypted files and broken URLs. Pay only for documents extracted.

HJL Analytics and AI development

PDF URL to Markdown, Tables & RAG Extractor

thescrapelab/Apify-PDF-url-scraper

Extract clean Markdown, page text, tables, metadata, summaries, and AI-ready RAG chunks from PDF URLs.

Inus Grobler

PDF to Structured Markdown Converter

automation-lab/pdf-to-structured-markdown-converter

Convert PDFs into page-aware Markdown with typed headings, paragraphs, lists, links, simple tables, bounding boxes, and embedded-image references.

Automation Lab

PDF to Markdown & JSON Extractor for LLMs

f0rty7even/pdf-extractor

Turn any PDF URL into clean, LLM-ready Markdown and structured JSON. Extracts text + tables + document metadata for RAG, agents, and fine-tuning. No AGPL components.

Michael Yousrie

URL to Clean Markdown for LLMs & RAG

eltociear/url-to-markdown-for-llms

Convert a webpage to Markdown and extract the main content from any URL. Turns HTML into clean Markdown for LLM context and RAG ingestion: strips nav, ads and boilerplate, keeps headings, lists and tables, returns title, byline, date and word count. No headless browser. Pay per page extracted.