Enables AI assistants to create, read, and manipulate Microsoft Word documents with comprehensive formatting, table creation, content management, and document protection capabilities. Supports advanced operations like merging documents, PDF conversion, and rich text formatting through a standardized interface.
An MCP server that enables text extraction and replacement in Microsoft Word documents by directly automating the Word application on Windows. It supports processing content across headers, footers, tables, and shapes using the pywin32 library.
A MCP stdio server shim around common yFinance calls.
Enables AI assistants to search the web, get news, perform research, and retrieve AI-powered answers with citations using the You.com API.
A Model Context Protocol server that enables retrieval of transcripts, metadata, and subtitles from YouTube videos. It supports multiple languages, automatic paragraph segmentation, and video downloading to facilitate content analysis and processing.
MCP Server for ZeroEntropy collections, top documents and rerankers
An MCP server that provides offline access to ZIM file archives, including Wikipedia, medical knowledge, and maps. It dynamically exposes tools like search, article retrieval, and driving route planning based on available ZIM files.
Enables converting Markdown text into high-quality 3:4 ratio JPG images using multiple rendering backends. Supports intelligent fallback between imgkit/wkhtmltopdf, markdown-pdf, and PIL rendering engines with customizable styling options.
Enables access to IMDB movie and entertainment data through the Model Context Protocol. Note: The README describes a notes system but the project name suggests IMDB functionality.
Bidirectional Markdown ↔ Word (.docx) converter. Read Word documents directly into Claude as Markdown, or save Claude's output as a properly formatted .docx with heading styles (Title, Heading 1–9), bold, italic, tables, lists, code blocks, and images. No cloud upload — runs entirely on your machine using python.
MCP server for MDMA (Markdown Document with Mounted Applications) — interactive Markdown with forms, approval gates, tables, and more. Exposes the MDMA spec, authoring prompts, package metadata, and live docs to AI assistants so agents can author and integrate MDMA correctly.
Converts Markdown files and raw content into professionally styled PDFs with full support for Mermaid diagrams and syntax highlighting. It offers customizable page formats, margins, and modern typography for high-quality document generation.
Converts Markdown to styled PDFs using VS Code's markdown styling and Python's ReportLab, providing a simple note storage system with custom URI scheme.
An MCP server that enables bidirectional conversion between Markdown and PDF formats, including text extraction from specific pages and metadata retrieval. It supports customizable PDF output sizes and document processing through standard MCP tools.
Inline review comments for markdown specs and design docs. Agents request human review mid-task via MCP and pause until you send feedback.
Converts documents, webpages, and media files into markdown for AI assistants using Microsoft's MarkItDown and Crawl4AI. It enables tools to read PDFs, Office files, and JavaScript-rendered websites with support for OCR and image extraction.
An MCP server that converts Markdown files containing Mermaid diagrams into PDF documents by rendering diagrams as SVG images. It provides a specialized tool to automate document conversion while ensuring all visual charts are correctly embedded in the final output.
Exposes Mealie recipe manager as LLM-callable tools for searching recipes, managing meal plans, and editing shopping lists.
全面解析Medadapt Content ServerMCP Server的核心功能、安装配置和实用案例。作为顶级Model Context Protocol服务器，Medadapt Content Server能让AI助手访问实时数据、执行操作，为您提供更智能的工作体验和自动化解决方案。
安装状态
已补齐
命令预览
pip install -r requirements.txt进行安装。
Enables LLMs to interact with MediaWiki installations as a bot user, supporting page editing, searching, moving, deleting, comparing revisions, and retrieving site information through the MediaWiki API.
