"How to read and write in Microsoft Word" matching MCP servers:

A Model Context Protocol server that enables AI assistants to create, read, edit, and format Microsoft Word documents through standardized tools and resources.

A Model Context Protocol server that enables AI agents to access, search, and understand structured package documentation and source code from Git repositories. It automatically generates specialized tools to browse module overviews, components, and detailed documentation for technical libraries.

A local MCP server that lets LLM agents read EPUB books and PDF documents with outline-first navigation, precise node reads, and local SQLite persistence.

Enables reading and analyzing Word documents with advanced features including table extraction, OCR image analysis, full-text search, and intelligent caching for optimized performance on large documents.

Enables PDF reading through MCP with text extraction, Chinese OCR for scanned documents, page rendering, and keyword file search from any compatible MCP client.

An MCP server that enables programmatic interaction with Microsoft Word documents on Windows via COM Interop, allowing operations like document creation, text manipulation, formatting, and table management.

Enables AI agents and MCP clients to fetch webpages, strip noise, and convert them into clean, token-efficient Markdown. Supports optional crawling, caching, robots.txt compliance, and link preservation.

MCP server to read protected (or unprotected) PDF files, extracting text to a temp file, and handling large PDFs.

Enables AI agents and LLM pipelines to fetch and crawl websites locally, extract readable content, and convert pages into clean Markdown with preserved links while minimizing token usage.

A Model Context Protocol server that converts Markdown documents to plain text with flexible options and dual protocol support.

Enables users to turn any API's documentation into a tested MCP server whose tools expose the API's own operations, with linting, contract tests, and live verification. It accepts OpenAPI/Swagger, Postman, RAML, WSDL, GraphQL, RSS, and HTML docs.

Enables searching and retrieving documentation from crawled documentation sites as an MCP server, allowing coding agents to query real docs instead of relying on training data.

Converts Markdown files to Atlassian Document Format and publishes them to Confluence, with support for rendering Mermaid diagrams as PNG attachments.

Converts any OpenAPI/Swagger spec into an MCP server, exposing REST API endpoints as tools for Claude.

Enables converting Markdown text into clean HTML for headings, lists, code blocks, tables, links, and images, with optional full-document wrapping via x402 micropayments.

A minimal MCP server that auto-generates tools from your OpenAPI spec, optimized for Vercel.

A Cloudflare Worker that transforms Cloudflare AI Search (AutoRAG) instances into an MCP server for querying documentation. It enables AI models to search and retrieve relevant information from custom document sets stored in R2 buckets.

Enables local conversion of PDFs to Markdown, with automatic OCR fallback for scanned pages, image extraction, and page-by-page structure preservation.

Enables converting a public release-note URL into ordered upgrade tasks with source excerpts, anchors, confidence, and uncertainty, without executing release text or project code.

Fetches website content and converts it to Markdown format with AI-powered content cleanup, ad removal, and full OpenAPI/Swagger specification support for easy processing by AI assistants.

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.

Provides LLMs with real-time access to up-to-date documentation from PyPI, npm, crates.io, GoDocs, DockerHub, GitHub, and GCP, preventing outdated code generation and API hallucinations.

Converts documents (PDF, Word, PPT, images, HTML) to Markdown via MinerU API. Supports URL and local file inputs with OCR, formula/table recognition, and automatic large file handling.

The Microsoft Learn Docs MCP Server is a cloud-hosted service that enables clients like GitHub Copilot and other AI agents to bring trusted and up-to-date information directly from Microsoft's official documentation. It is a remote MCP Server using streamable http, which is lightweight for clients t

Enables building MCP servers using TypeSpec, with tools to scaffold, compile, and learn TypeSpec.

Exposes a small catalog of programming study topics through the Model Context Protocol (MCP) for local learning.

Enables AI assistants to analyze project folders for dependencies and frameworks and fetch current documentation or datasheets from the web.

A professional MCP server for analyzing content against the official Microsoft Writing Style Guide, enabling style, grammar, terminology, and accessibility checks via AI tools like VS Code and GitHub Copilot.

Enables interaction with Zhejiang University's learning platform (学在浙大 / 智云课堂) via MCP tools, allowing natural language commands to check todos, view schedules, fetch lecture transcripts, and submit homework.

Provides Large Language Models with real-time access to the latest documentation for Python libraries like Langchain, LlamaIndex, and OpenAI, enabling accurate and up-to-date code suggestions.