# PDF Parsing

GROBID MCP Server Project

The PDF Reader MCP service provides AI agents with a secure and flexible function to extract content from PDF files, including text, metadata, and page count information. It supports local and remote PDF files and is easy to integrate into the MCP environment.

This project builds an HR chatbot based on RAG. The MCP server serves as the functional call center to implement PDF document upload, parsing, retrieval, and natural language question answering functions.

An intelligent learning assistance system based on PDF document analysis, providing functions such as document conversion, content organization, and question generation to help users learn efficiently.

PDF Content Extraction Service

A server based on the Model Context Protocol (MCP) that provides access to clinical guidelines from the National Comprehensive Cancer Network (NCCN). This system ensures the accuracy and reliability of medical guidance by directly reading the PDF content of the guidelines instead of using RAG technology.

A service that assists users in learning by analyzing PDF documents, providing functions such as file conversion, content organization, and question generation.

Lizeur is a PDF content extraction server based on the MCP protocol. It uses Mistral AI's OCR technology to convert PDFs into readable Markdown text, supporting intelligent caching and rapid integration.

Zotero - MCP is a Python server that implements the integration of the Model Context Protocol (MCP) with the Zotero literature management software, enabling AI assistants to access and query users' Zotero literature libraries.