📚Complete Guide

Docling Tutorial: Get Started in 5 Minutes [2026]

Name: Docling
Brand: Docling

Master Docling with our step-by-step tutorial, detailed feature walkthrough, and expert tips.

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Getting Started with Docling

Install Docling with `pip install docling` (add `docling[ocr]` or `docling[vlm]` for OCR/VLM support). Parse your first document using the DocumentConverter API: `converter = DocumentConverter(); result = converter.convert('myfile.pdf')`. Export the parsed result to Markdown, JSON, or HTML using `result.document.export_to_markdown()` or similar export methods. Integrate with your RAG stack by installing the appropriate connector (e.g., `docling

langchain`, `docling

llamaindex`, or `docling

haystack`). For batch processing or automation, use the Docling CLI: `docling convert

to md ./documents/`.

💡 Quick Start: Follow these 5 steps in order to get up and running with Docling quickly.

🔍 Docling Features Deep Dive

Explore the key features that make Docling powerful for mcp / agent infrastructure workflows.

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❓ Frequently Asked Questions

Is Docling free to use commercially?

Yes. Docling is released under the Apache 2.0 license and the associated models (Docling layout, TableFormer, Granite-Docling, SmolDocling) are openly available on Hugging Face, so it can be embedded in commercial products and run on-premises without per-document fees.

What document formats does Docling support?

Docling parses PDF, DOCX, PPTX, XLSX, HTML, Markdown, AsciiDoc, CSV, and images (PNG, JPEG, TIFF), and recent versions add audio transcription. Outputs include Markdown, HTML, JSON, and the structured DoclingDocument schema.

How does Docling compare to using a hosted API like Unstructured or AWS Textract?

Docling runs locally with no data ever leaving your environment, which hosted APIs cannot offer. It also preserves richer structural information (tables via TableFormer, reading order, formulas) than most generic OCR APIs. The trade-off is that you operate the infrastructure yourself rather than paying per page.

Can Docling be used inside an AI agent or IDE assistant?

Yes. Docling ships a Model Context Protocol (MCP) server so MCP-compatible agents and IDE assistants (Claude Desktop, Cursor, etc.) can call it as a tool to convert and chunk documents on demand, in addition to direct integrations with LangChain, LlamaIndex, Haystack, and Crew AI.

Does Docling handle scanned PDFs and images?

Yes. It integrates with OCR engines including EasyOCR, Tesseract, and RapidOCR, and can run vision-language pipelines (SmolDocling, Granite-Docling) that read directly from page images to produce structured output.

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Tutorial updated March 2026

🔍 Docling Features Deep Dive

Explore the key features that make Docling powerful for mcp / agent infrastructure workflows.

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❓ Frequently Asked Questions