docling.rs

Name: docling.rs
Author: docling-project

by docling-projectversion 2.67.1i★ –iRuns on your computer

Registry nameio.github.docling-project/docling-rs

Install

Overview

Description from the maker (original English)

Documents to Markdown for agents: PDF layout, tables and OCR, Office, HTML, scans. docling in Rust.

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

User voiceiNo reviews yetReviews open together with accounts in a later step
Our basic checksi1 of 1 passedChecked from public information; code not scanned yet
UsageiNot measured yet★ –

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

Connection: Runs on your computer
Transport: stdio
Category: Docs, sheets & office work

Install

Pick the AI app you use, then copy the settings.

Before you install

Basic checks: 1 of 1 passed
Runs on your computer with your user’s permissions (files, network, apps).
You fill in yourself: DOCLING_RS_CACHE_DIR, DOCLING_RS_OCR_LANG

You need

PyPIPython’s uv installed (for the uvx command)

Which app do you use?

ClaudeClaude CodeCursorVS CodeChatGPT

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

{
  "mcpServers": {
    "docling-rs": {
      "command": "uvx",
      "args": [
        "docling-rs-mcp",
        "--root",
        "your-value",
        "--allow-url-fetch",
        "false"
      ],
      "env": {
        "DOCLING_RS_CACHE_DIR": "your-value",
        "DOCLING_RS_OCR_LANG": "your-value"
      }
    }
  }
}

Run this in your terminal

claude mcp add docling-rs --env DOCLING_RS_CACHE_DIR=your-value --env DOCLING_RS_OCR_LANG=your-value -- uvx docling-rs-mcp --root your-value --allow-url-fetch false

Fill in the empty values before running it.

This one needs values on its command line, so copy the settings and fill them in.

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "docling-rs": {
      "command": "uvx",
      "args": [
        "docling-rs-mcp",
        "--root",
        "your-value",
        "--allow-url-fetch",
        "false"
      ],
      "env": {
        "DOCLING_RS_CACHE_DIR": "your-value",
        "DOCLING_RS_OCR_LANG": "your-value"
      }
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one needs values on its command line, so copy the settings and fill them in.

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "docling-rs": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "docling-rs-mcp",
        "--root",
        "your-value",
        "--allow-url-fetch",
        "false"
      ],
      "env": {
        "DOCLING_RS_CACHE_DIR": "your-value",
        "DOCLING_RS_OCR_LANG": "your-value"
      }
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

Values you fill in

DOCLING_RS_CACHE_DIR env
Where `docling-rs-mcp --download-models` puts the PDF/image models and the server finds them (default ~/.cache/docling.rs).
DOCLING_RS_OCR_LANG env
OCR language for scans: en (default), ch, or a BCP-47 tag.

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 7, 2026

✓ Pass
Maker matches the repo
The registry name was verified with the GitHub account docling-project, which owns the repo
… Not checked yet
Still maintained
We have not read this repo from GitHub yet
… Not checked yet
Has a licence
We have not read this repo from GitHub yet
– Not applicable
Endpoint responds
This one runs on your computer; there is no internet endpoint
– Not applicable
Sign-in with OAuth
Runs on your computer and uses local settings instead
… Not checked yet
No hidden instructions in tool descriptions
Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Docs, sheets & office worki

More stars than 0% of the other 2187 servers in this category
Published to the registry more recently than 95% of the other 2187 servers in this category
Basic checks equal to or better than 100% of the other 2187 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is docling.rs safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

The registry does not list a required key, though some servers ask you to sign in on first use.

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (2.67.1) reached the registry today.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Python (uv), Docker on your computer.

What can I use instead?

In the same category: Agent-Native Calendar, Excel MCP Server, MCP Server for Excel

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Install

README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

docling.rs

docling.rs converts documents — PDF, Office, HTML, scans, audio — into Markdown, docling JSON and the other shapes an LLM or a RAG pipeline can read. It is a Rust port of IBM's docling: the same output, byte-for-byte, from one static binary. No Python, no PyTorch.

Pulling text out of a PDF is easy. Keeping its *structure* — headings in order, tables as tables, scanned pages read — takes layout analysis, table recognition and OCR. docling has the models for that, and a Python stack to match. docling.rs runs the same models from a single binary: PDF 4.3× faster than Python docling at under half the RAM, Office and HTML 20–60× faster, and tables that survive — cell recall 0.94 where MarkItDown gets 0.31 (numbers, method).

Coming from [MarkItDown](https://github.com/microsoft/markitdown)? pip install docling-rs, swap one import — from docling_rs.markitdown import MarkItDown — and keep its API, every format it converts included, with real layout analysis, tables and OCR behind it: guide, measured side by side.

Coming from [Marker](https://github.com/datalab-to/marker)? pip install docling-rs, swap the imports — from docling_rs.marker.converters.pdf import PdfConverter — and keep its API: create_model_dict, text_from_rendered, the JSON block tree, chunks, marker_single's CLI and output layout, with docling's layout analysis, TableFormer and OCR behind it and no PyTorch or inference server: guide, measured side by side.

Coming from [MinerU](https://github.com/opendatalab/MinerU)? pip install docling-rs, swap the imports — from docling_rs.mineru.parser import parse — and keep MinerU 4's SDK: ParseResult, markdown(), the Middle JSON, Content Lists and Structured Content, save()'s layout and mineru-kit parse, with docling's layout analysis, TableFormer and OCR behind it and no DocVortex or llama.cpp: guide, measured side by side.

Install

# CLI + models (Linux x64/arm64/s390x + macOS arm64 prebuilt; builds from source elsewhere)

curl -fsSL https://raw.githubusercontent.com/docling-project/docling.rs/master/scripts/install/install.sh | bash docling-rs example.pdf # Markdown on stdout

or from crates.io; --cli puts the models where the installed binary looks

cargo install docling-cli curl -fsSL https://raw.githubusercontent.com/docling-project/docling.rs/master/scripts/install/download_dependencies.sh | sh -s -- --cli

pip install docling-rs # Python — drop-in for docling's, MarkItDown's, Marker's and MinerU's APIs npm install docling.rs # Node.js / Bun cargo add docling # Rust library

containers, models baked in (-cuda variants for NVIDIA)

docker run --rm -v "$PWD:/data" ghcr.io/docling-project/docling-rs paper.pdf docker run -p 127.0.0.1:5001:5001 ghcr.io/docling-project/docling-rs-serve

Office, HTML, Markdown and e-mail need no models. PDF, images and audio need the ONNX models (layout, OCR, TableFormer, Whisper; under 1 GB): install.sh, --cli and the containers bring them along; with pip, run python -c "import docling_rs; docling_rs.download_models()" once; with npm or a checkout, run download_dependencies.sh where you convert (details). Windows: docs/WINDOWS.md.

▶ [Try it in your browser](https://docling-project.github.io/docling.rs/) first — the converter as wasm, OCR included; nothing leaves your device.

Use

docling-rs report.pdf > report.md               # Markdown (streamed page by page)

docling-rs report.pdf --to json # docling JSON; also html, text, latex, dclx, chunks, images docling-rs --input ./docs --output ./out # a directory tree; --jobs N in parallel docling-rs https://example.com/paper.pdf # URLs, data: URIs and stdin (-) too docling-rs https://www.youtube.com/watch?v=ID # a YouTube video: title, description, caption transcript (--to vtt keeps the timing) docling-rs --help # every flag: OCR, page ranges, images, enrichment, redaction …

from docling_rs import DocumentConverter       # was: from docling.document_converter import …

doc = DocumentConverter().convert("report.pdf").document print(doc.export_to_markdown())

import { convertFileAsync } from 'docling.rs'

const { content } = await convertFileAsync('report.pdf', { to: 'markdown' })

use docling::{DocumentConverter, SourceDocument};

let result = DocumentConverter::new().convert(SourceDocument::from_file("report.pdf")?)?; println!("{}", result.document.export_to_markdown());

curl -F file=@report.pdf 'localhost:5001/v1/convert?to=md'   # the server; OpenAPI at /openapi.yaml

Same options, same outputs on every surface — every option in docs/OPTIONS.md.

Highlights

From Python docling: from docling_rs import DocumentConverter; result.document is a genuine DoclingDocument (migration notes).
Every docling format, and a few it lacks — the table under Status, each validated against live docling (Conformance).
Every output docling has: Markdown (docling's, or a stricter dialect), docling JSON, HTML, plain text, DocLang, LaTeX, Pandoc AST (→ DOCX, EPUB, Typst… through pandoc), WebVTT subtitles, RAG chunks and page images (output formats).
From any language: Rust, Python, Node.js / Bun, the browser (wasm, fully client-side), C, C++, C#, Go, Java and Swift through one C header, any HTTP client, the shell (Integration).
A drop-in server for docling-serve: Open WebUI uses it as its Docling content-extraction engine — point *Docling Server URL* at http:// :5001 — and n8n, Dify and LangChain clients work unchanged (docling-rs serve, Open WebUI setup).
AI agents (MCP): docling-rs mcp gives Claude Desktop, Claude Code, Cursor or VS Code MarkItDown's convert_to_markdown tool, plus convert for JSON, chunks and the rest — uvx docling-rs-mcp, or claude mcp add docling -- docling-rs mcp (MCP server).
LangChain: pip install "docling-rs[langchain]" — langchain-docling's DoclingLoader on the Rust engine, one import to swap (details).
AutoGen: pip install "docling-rs[autogen]" — DoclingIndexer fills any AutoGen memory with chunks that carry their pages, DoclingConvertTool lets an agent read documents (details).
Microsoft Agent Framework: pip install "docling-rs[agent-framework]" — AutoGen's successor: DoclingIndexer fills any Agent Framework vector store, DoclingContextProvider puts the relevant chunks with their pages into each turn (details).
Your own formats: register a backend for a format docling.rs does not read — or to read one of its formats your way — from Rust, Python (@docling_rs.register_backend(extensions=["rtf2"]), and MarkItDown's register_converter and plugins) or Node.js, ahead of the built-in formats (pluggable backends).
RAG: docling-rag — chunk, embed and search with a REST API and a web UI (RAG subsystem).
Runs where you are: Linux x64 / arm64 / s390x, macOS (Apple Silicon) and Windows prebuilt (CLI, wheels, npm), Intel macs from source, containers for amd64 and arm64; NVIDIA CUDA and TensorRT, DirectML (a prebuilt Windows CLI), CoreML and WebGPU in the browser as opt-in accelerators (GPU, IBM Z).

Developed with Claude Code and _TENET_ (minimalistic AI-driven development framework).

Status

Every format in docling's pipeline converts — plus a few docling lacks. A file with no or an unknown extension, stdin, an upload or a data: URL is typed by its content (InputFormat::detect, docling_rs.detect_format, detectFormat: the packages, the OLE files, PDF, images, audio and video, iWork, XML, JSON, notebooks, messages, …), and a file that fails under its extension is checked by content and converted as what it really is, with a warning.

Category	Formats
Text & markup	Markdown, AsciiDoc, HTML, MHTML, LaTeX (multi-file arXiv projects, math, tables); plain text and source code (`.py`, `.yaml`, `.log`, … — any text file, as a code block or paragraphs), generic JSON / JSON Lines and XML (kept as code blocks); RSS / Atom / RDF feeds (`.rss`, `.atom`, `.rdf` or a bare `.xml`: the feed's title, each item's heading, date and body); Jupyter notebooks (`.ipynb`: markdown cells, code cells in the kernel's language, outputs on request)
Word processing	DOCX, Word 97–2004 `.doc` (and Word 6/95, 1.x/2.0), ODT, OpenOffice / StarWriter, AbiWord, WordPerfect, MS Works, Hancom HWP / HWPX, Lotus Word Pro, MacWrite / Word for Mac / ClarisWorks, T602, Palm e-texts, print files (`.prn`), EPUB, RTF
Presentations	PPTX, PowerPoint 97–2003, ODP, OpenOffice / StarImpress
Spreadsheets	XLSX, XLSB, Excel 97–2004, ODS, CSV / TSV, dBase, DIF, SYLK, Lotus 1-2-3, Quattro Pro, MS Works, Kingsoft `.et`
Diagrams · Apple iWork	Visio, SVG, CGM (its text) · Pages, Numbers, Keynote
PDF & images	PDF (layout, TableFormer, OCR), PNG, JPEG, TIFF, BMP, WebP, GIF, HEIC (opt-in), METS/GBS scans, DjVu

| XML · docling native | JATS, USP

Only the beginning is shown; read the rest in the repo

docling.rs

Overview

PopNx MCP’s three pillars

What you can do with it

Install

Before you install

Values you fill in

What it can do

Basic checksi

Maker matches the repo

Still maintained

Has a licence

Endpoint responds

Sign-in with OAuth

No hidden instructions in tool descriptions

Compared with others in Docs, sheets & office worki

Common questions

Alternatives

Agent-Native Calendar

Excel MCP Server

MCP Server for Excel

README from the maker

docling.rs

Install

or from crates.io; --cli puts the models where the installed binary looks

containers, models baked in (-cuda variants for NVIDIA)

Use

Highlights

Status