Extract structured text, metadata, tables, and images from mixed documents through an MCP server with Kreuzberg

Expose one document-extraction surface to MCP-compatible agents so they can normalize PDFs, Office files, images, HTML, and other mixed inputs before downstream review or indexing.

Prerequisites

Kreuzberg install or container image, document files to process, MCP-compatible client

Installation

Use the upstream install or setup path that matches your environment:

• npx skills add kreuzberg-dev/kreuzberg

Requirements and caveats from upstream:

• <img src="https://img.shields.io/pypi/v/kreuzberg?label=Python&color=007ec6" alt="Python">
• <a href="https://www.npmjs.com/package/@kreuzberg/node">
• <img src="https://img.shields.io/npm/v/@kreuzberg/node?label=Node.js&color=007ec6" alt="Node.js">

Basic usage or getting-started notes:

• Each language binding provides comprehensive documentation with examples and best practices. Choose your platform to get started:

• Scripting Languages:

• Ruby – RubyGems package, idiomatic Ruby API, native bindings

• Source: https://github.com/kreuzberg-dev/kreuzberg

• Extracted from upstream docs: https://raw.githubusercontent.com/kreuzberg-dev/kreuzberg/HEAD/README.md

Documentation

• https://github.com/kreuzberg-dev/kreuzberg#readme

Source

• Agent Skill Exchange