"How to read content from a Word document" matching MCP servers:

Enables AI assistants to create and manipulate Microsoft Word documents programmatically with support for rich text formatting, tables, lists, headings, and find-and-replace operations.

A consolidated MCP server for creating, reading, and manipulating Microsoft Word documents with 25 tools including search/replace, track changes, and document protection.

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 programmatic generation of Microsoft Word documents (.docx) from AI-generated text and data, with support for Markdown formatting, tables, headers, and rich document elements that are saved directly to the local file system.

Structure-preserving Word DOCX editing MCP server with a .NET Open XML backend and Office.js live sessions. Enables safe, auditable, incremental editing of Microsoft Word documents for AI agents.

Enables reading, creating, and appending content to Microsoft Word (.docx) files through natural language commands.

Enables AI agents to edit Word documents using track changes, allowing lawyers to review each modification via Word's revision interface.

An MCP server that exposes documents.js's document conversion, .odb, metadata, and font tooling as MCP tools, enabling agents to convert, inspect, and edit a wide range of document formats over stdio.

MCP server enabling Claude Code to capture screenshots of Windows applications through WSL2, allowing AI to diagnose UI errors and verify layouts.

Enables AI assistants to directly read, edit, and manipulate Word documents, supporting image and table operations, paragraph editing, and search/replace.

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.

Enables creation of word cloud visualizations from various document formats (PDF, Word, TXT, MD) with intelligent text extraction, customizable themes, and multiple output formats (SVG, PNG, JPG, WebP).

A Model Context Protocol server for enterprise-grade document automation, enabling AI assistants to create, read, manipulate, and analyze Microsoft Word documents programmatically.

Enables AI assistants to create, read, edit, and analyze Microsoft Word documents through a standardized protocol, covering headings, paragraphs, lists, images, tables, styling, footnotes, comments, document protection, and PDF conversion. It also supports advanced manipulation such as inserting content relative to existing text, search-and-replace, custom styles, and detailed table and cell formatting.

Enables MCP clients to extract text from PDF, image, Word, PowerPoint, and Excel files using MinerU, either on the local machine or a self-hosted private-network API. Parsed results are saved locally as Markdown, structured JSON, and extracted images, which can then be read back in segments.

A Windows MCP server that attaches to a running Microsoft Word instance via COM automation and exposes 20 tools for reading, editing, formatting, and exporting documents — live on screen.

A personal MCP bridge that lets ChatGPT drive a local Codex CLI, translating instructions into Codex app-server threads and returning compact summaries of what Codex did.

MCP server for real-time Microsoft Word document manipulation via COM automation. Word runs in a visible window — every change appears instantly.

A fully working MCP server built from scratch in plain Node.js, implementing tools, resources, prompts, notifications, and sampling according to the MCP specification, designed to connect to Claude Desktop or any MCP client.

A no-server MCP toolkit that organizes project wikis from Feishu documents, messages, and more, enabling AI clients to answer questions with cited evidence to prevent hallucinations.