DEVOURED
Xberg (GitHub Repo)
Xberg is a high-performance, Rust-based engine that extracts structured data and metadata from 101 file formats using local or remote LLMs.
What: Xberg handles OCR, transcription, table extraction, and code analysis across 115 file extensions. It runs via CLI, REST API, or as an MCP server, supporting 15 language bindings without requiring a GPU.
Why it matters: It addresses the fragmentation of document-processing pipelines by unifying detection, extraction, and embedding generation into a single engine designed for RAG workflows.
Deep dive
- Unified Pipeline: Eliminates the need to chain multiple libraries for format detection, OCR, and chunking.
- Breadth of Support: Processes 101 formats including Office docs, images, audio, video, and 371 programming languages.
- Deployment Flexibility: Offers a CLI, library bindings (Rust, Python, Node.js, Go, etc.), and a Docker-ready REST API.
- AI Features: Supports local or hosted LLMs for structured extraction and local embeddings for semantic search.
- Agentic Integration: Built-in MCP (Model Context Protocol) server allows integration with tools like Claude Desktop and Cursor.
Decoder
- MCP (Model Context Protocol): An open standard that enables AI assistants to securely connect to data sources and tools.
- Tree-sitter: A parser generator tool used for incremental, high-performance code parsing and syntax analysis.
- FFI (Foreign Function Interface): A mechanism for a program written in one language to call routines or use services written in another.
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