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Context7 MCP Fc0c966e

A Model Context Protocol server that fetches up-to-date, version-specific documentation and code examples from libraries directly into LLM prompts, helping developers get accurate answers without outdated or hallucinated information.

Cosa Sai

全面解析Cosa SAI (Gemini Docs)MCP 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，Cosa SAI (Gemini Docs)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。

DocGen MCP Server

Automates the creation of standardized documentation by extracting information from source files and applying templates, with integration capabilities for GitHub, Google Drive, and Perplexity AI.

Dumpling AI MCP

全面解析Dumpling AIMCP 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，Dumpling AI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。

Feishu MCP Server (Sdd330)

An MCP-based service that enables AI models to seamlessly interact with Feishu (Lark) platform, supporting document reading and chatbot messaging capabilities.

Provides an agent-first note-taking system designed from the ground up for AI collaboration. Organizes your notes as a local vault of ordinary markdown files with semantic note types.

iReader MCP

Enables extraction of content from various web sources including webpages, YouTube transcripts, tweet threads, PDF files, and public Google Docs. It provides specialized tools to convert internet resources into markdown or text for model consumption.

Keynote MCP

MCP server that gives AI full control over Apple Keynote through AppleScript automation. Create, edit, and export presentations via natural language with 30+ tools.

A Model Context Protocol server that enables AI agents to interact with a local Logseq instance, allowing operations like creating pages, managing blocks, and searching across a knowledge graph.

Enables real-time indexing and semantic search of local documents (PDF, Word, text, Markdown, RTF) using vector embeddings and local LLMs. Monitors folders for changes and provides natural language search capabilities through Claude Desktop integration.

MCP Google Docs (mcp-google-docs)

mcp server for creating, reading, editing google docs (supports comments)

MCP Notes (9 Ninety)

A simple note-taking MCP server for recording and managing notes with AI models.

MCP Tasks Organizer

An MCP server that converts Cursor agent plans into structured markdown task lists and organizes them in your repository, helping you track AI-generated plans and recommendations as actionable specifications.

Convert Markdown to DOCX, PDF, and HTML using your own Word templates — your letterhead, your branding, your fonts. Plus 15 designer-built templates for when you don't have your own. MDMagic plugs straight into Claude, Cursor, VS Code, and any MCP-compatible AI assistant, giving them direct access to a professional document conversion pipeline - and, more importantly, *your* templates. ✨ Use your own Word templates Upload your existing letterhead, stationery, brand guidelines, contract shells, proposal templates — anything you already use in Microsoft Word. Once uploaded, your AI assistant can convert any Markdown directly into a polished document carrying *your* logo, fonts, colours, footers, page numbers, watermarks, and signature blocks. The output looks like it came from your design team, not from a generic AI export. 🎨 Or pick from 15 designer-built templates Don't have a Word template ready? MDMagic ships with 15 professionally designed templates across four categories: • Business — Executive Platinum, Financial Blue, Premium Bronze, Professional Azure, Business Purple • Creative — Designer Indigo, Artistic Aqua, Sunset Vibes, Sage Serenity, Minimalist Pro, Cheese Burger • Professional — Legal Burgundy, Modern Legal • Technical — Code Documentation, Deep Data Blue 🧰 Ten tools, designed for AI workflows • convert_document — Markdown → DOCX, PDF, HTML, or all three • validate_markdown — pre-flight syntax check before you spend credits • estimate_conversion_cost — know the cost before the conversion runs • recommend_template — describe the document, get the right template • list_all_templates / list_builtin_templates / list_custom_templates — full catalogue with category filters • get_template_details — confirm page sizes, orientations, variants • check_credit_balance — credits remaining, plan status, cost-aware AI behaviour • show_default_settings — honour the user's preferred page size and orientation 💸 Same credits, one balance Whether you convert via the MDMagic web app or your AI assistant, credits work the same way. Free-tier credits renew monthly. Paid plans and one-off top-ups available. The MCP refuses conversions when your balance is low — no surprise bills. 🚀 Five-minute setup Sign up at https://mdmagic.ai/account → grab your API key → paste a JSON snippet into your AI client's MCP config → restart. Done. The hosted endpoint at https://api.mdmagic.ai/mcp is also available for clients that don't run local processes. Built for serious documents. Designed for AI assistants. Trusted with your brand.

全面解析Memory Bank MCPMCP 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，Memory Bank MCP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。

Notebooklm MCP (notebooklm-mcp-server)

Enables automated interactions with Google's NotebookLM through browser automation. Supports persistent sessions, document uploads, notebook management, and streaming chat responses for AI-powered document analysis.

A Model Context Protocol server that integrates with Nutrient Document Web Service, allowing AI assistants to perform advanced PDF operations including digital signing, document generation, editing, OCR, watermarking, and redaction.

Enables interaction with Obsidian vaults through MCP, supporting note creation from templates, link management, backlink analysis, tag operations, and automatic Map of Contents generation.

Office Word MCP Server (Gong Rzhe)

全面解析Office Word MCP 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，Office Word MCP 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。

Enables LLMs to chat with long PDFs using a reasoning-based, tree-structured document index that navigates content like a human would, without requiring vector databases or hitting context limits.