"Information about the DOCX file format or tools for handling DOCX files" matching MCP servers:

Legal document redlining engine that applies AI-generated JSON changes as professional tracked changes with comments in .docx files, producing Word-indistinguishable output.

An MCP server for reading, editing, and validating Microsoft Word documents with specialized support for track changes, comments, and footnotes. It enables structural auditing, heading extraction, and precise OOXML-level document manipulation through natural language tools.

Provides comprehensive read/write access to Word documents, including comments, track changes, and reply threads.

MCP server for Word document (.docx) creation and manipulation — the production-grade document automation tool for AI agents.

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.

Enables AI agents to create, read, and edit Word documents with tracked changes, comments, and template manipulation, including bulk text replacement and paragraph-level operations.

A Word document processing MCP server that exposes a single tool (docx_process) routing to 63 operations covering creation, editing, formatting, and querying, with on-demand skill loading for context efficiency.

An MCP server that provides information about Utkarsh, including bio, skills, work experience, and portfolio projects, accessible via local stdio or remote HTTP with OAuth.

Enables comprehensive management of Microsoft Word documents with 30+ tools for reading, writing, formatting, template merging, image extraction, equation extraction, and style application.

A lightweight MCP server for basic file operations, enabling reading, writing, and listing files securely via the Model Context Protocol.

An MCP (Model Context Protocol) server that gives AI agents live, structured ad intelligence across Facebook, Google, and Instagram — data that no base model can produce from training alone. Powered by Apify actors. Works with any MCP-compatible client: Cursor, Claude, etc.

Generates test files locally (images, PDFs, CSVs, corrupted files, etc.) from natural language prompts, with configurable sizes and safety limits.

Enables local analysis of unstructured documents (PDF, DOCX, PPTX, SVG, PNG) by extracting text and structure with citation anchors, and verifies summaries against source material before a human approves saving a report.

MCP server for managing i18n translation files — gives your AI agent full control over your app's translations without dumping entire locale files into context.

A secure MCP server for converting documents between Markdown, DOCX, HTML, PDF, and TXT formats within a sandboxed working directory.

Enables local file management through natural language interactions using the Gemini API, with tools for listing, reading, writing, deleting, and updating files.

Enables listing, reading, and searching local files and directories through MCP tools.

Enables structured learning with a verified loop: define goals as observable claims, learn through teach-lab-test-gate per claim, and get independently graded by an adversarial examiner to ensure genuine progress.

Enables fast file search on macOS using the native mdfind (Spotlight) command, with support for filtering, regex, sorting, and limiting results.

A read-only MCP server that provides document awareness for agents by parsing local files into structured profiles, blocks, chunks, and search results, enabling agents to understand and cite document content without dealing with raw file formats.