This project provides open-source components for ingesting and pre-processing unstructured data into structured outputs for large language models. It offers modular document partitioning across multiple file types and includes a Model Context Protocol server for agent-based file transformation.
Project overview
This project provides open-source components for ingesting and pre-processing unstructured data into structured outputs for large language models. It offers modular document partitioning across multiple file types and includes a Model Context Protocol server for agent-based file transformation.
Project type
MCP · Document Processing · Data Processing
Use cases
Documents & Office · Knowledge Q&A
Deployment
Python environment
License
Apache-2.0
Best for
Developers, AI engineers, and data teams who need to transform unstructured documents into structured data elements using a Python library or an MCP server.
Key capabilities
Provides modular functions to ingest and pre-process images and text documents like PDFs and HTML, automatically detecting file type and routing it to the appropriate file-specific partitioning function.
A server that gives agents the ability to turn 60+ file types into structured data by parsing, enriching, chunking, and embedding files.
Limitations and risks
Setup requires installing specific system dependencies like libmagic-dev and poppler-utils depending on the document type.
Coding is required to utilize the library, posing a barrier for non-technical users.
GPU and minimum hardware requirements are not documented.
Getting started
Install the Python SDK via pip, run a partition function on a test document, and print the string representation of the output. Note that installation requires specific system dependencies like libmagic-dev and poppler-utils based on document type.
Evidence and sources
GitHub project description: Convert documents to structured data effortlessly. Unstructured is open-source ETL solution for transforming complex documents into clean, structured formats for language models.
README: The `unstructured` library provides open-source components for ingesting and pre-processing images and text documents, such as PDFs, HTML, Word docs, and many more.
README: Unstructured Transform brings production-grade document processing to your agents as an MCP server. It gives them the ability to turn 60+ file types into structured data that's re…
README: Transform works with virtually any MCP-compatible host or agent framework — Claude Code, Cursor, Codex CLI and more.
README: Ready to move your data processing pipeline to production, and take advantage of advanced features? Check out Unstructured Pipelines. In addition to better processing performance,…