Kreuzberg is a polyglot document intelligence framework with a Rust core that extracts text, metadata, and structured information from PDFs, Office documents, images, and 106+ formats across 140 file extensions. It is designed for RAG pipelines and agent workflows, with async-first Python bindings, multiple OCR backends, and an MCP server mode.
Why It's in Assess
RAG pipeline enabler: Agents that need to read documents — PDFs, DOCX, spreadsheets, images with OCR — need a text extraction layer. Kreuzberg fills this gap with a lightweight, local-first approach (no API calls, no cloud dependencies).
MCP server mode: Can run as an MCP server, making document extraction directly available to MCP-capable agents — a natural fit for agentic workflows.
Performance advantage: Rust core delivers 10–50x speed improvement over Python-only alternatives. Installation footprint is 71MB versus Docling's 1GB+.
Broad format support: 88+ formats including PDF, DOCX, XLSX, PPTX, EPUB, HTML, images (with Tesseract, EasyOCR, or PaddleOCR backends).
Now branded "xberg": The project has moved its GitHub repo and docs to the xberg brand (repo xberg-io/xberg, docs at docs.xberg.io) while the PyPI package remains kreuzberg (v4.10.3 as of September 2026). Assess is unchanged — evaluate for your RAG pipeline, but the connection to coding agents specifically is indirect. Assess — evaluate for your RAG pipeline, but the connection to coding agents specifically is indirect.
