#parser

Parse and generate VFX industry file formats via MCP. Round-trip stable Nuke .nk, MaterialX .mtlx, and USD ASCII .usda parsing — pure transforms, no filesystem access, zero native dependencies.

Parse, explain, validate, generate, diff, and convert HL7 v2 messages. Supports versions 2.3-2.8 with 600+ CARISTIX field definitions. Bidirectional HL7 v2 to FHIR R4 conversion. 9 tools.

This project exposes the powerful Chepy data transformation library as an MCP server. It allows you to access Chepy's tools (like encoding, decoding, and data manipulation) via a single flexible API: the bake pipeline tool, inspired by CyberChef.

This project exposes the powerful Chepy data transformation library as an MCP (Model Context Protocol) server. It allows you to access Chepy's tools (like encoding, decoding, and data manipulation) via a single flexible API: the bake pipeline tool, inspired by CyberChef.

Simple RSS reader MCP Server

A Model Context Protocol (MCP) server enabling AI agents to intelligently search, retrieve, and analyze biomedical literature from PubMed via NCBI E-utilities. Includes a research agent scaffold. STDIO & HTTP

MCP server for parsing data from a pdf url

📚✨ A powerful MCP (Model Context Protocol) server that brings Readium's documentation analysis capabilities to LLMs like Claude and other MCP-compatible clients. 🤖🔍 Seamlessly analyze local directories, public/private Git repositories, and URLs with support for multiple file formats (code, Markdown, text). Readium-MCP delivers structured results with summary, file tree, and content organization—making it the perfect tool when you need an AI to comprehend large documentation bodies, code repositories, or technical websites. 🧠💻 Easy to integrate with VSCode, Claude Desktop, or any MCP client for enhanced AI-powered documentation analysis!

An MCP server built with Node.js/TypeScript that allows AI agents to securely read PDF files (local or URL) and extract text, metadata, or page counts. Uses pdf-parse.

An MCP server built with Node.js/TypeScript that allows AI agents to securely read PDF files (local or URL) and extract text, metadata, or page counts. Uses pdf-parse.

A lightweight implementation of the Model Context Protocol (MCP) server using Server-Sent Events. Features a Wikipedia article parser that converts content to Markdown format. Demonstrates client-server MCP communication over HTTP.

An MCP server built with Node.js/TypeScript that allows AI agents to securely read PDF files (local or URL) and extract text, metadata, or page counts. Uses pdf-parse.

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