"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.

Enables local .docx files to be managed with verified writes, returning before/after evidence for every mutation, plus PDF export and lock/sync status checks.

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 reading, creating, and editing Microsoft Word .docx documents through natural language, including text and table manipulation, cell merging, shading, borders, and table layout controls, plus font, paragraph, and list formatting. Supports extracting paragraph text and tables, appending headings and paragraphs, find-and-replace, and row, column, and table restructuring.

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

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.

Enables an AI assistant to search real card data, check legality and points, validate or save decks, pull rulings, and review tournament meta for TCG Advanced and Genesys. It exposes tools for card search, archetype lookup, deck validation, meta snapshots, and optional turn-1 line search.

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.

Enables adding footnotes, in-text citations, and a bibliography/works-cited section to Word .docx files without Word, supporting APA 7, MLA 9, and Chicago 17 styles.

Enables AI agents to perform local video, audio, and file operations inside an isolated workspace, including cutting/concat videos, extracting audio, transcribing, and managing files, with typed responses and background job support.

Six local CPU MCP tools for Markdown/HTML-to-PDF conversion, PDF text extraction, safe SVG-to-PNG rendering, and PDF link and chapter inspection. Linux/WSL2; no GPU, hosted inference API, or model download required.

Enables Claude Cowork on Windows to read, write, edit, list, find, and regex-search files inside a WSL distribution over stdio, accepting Windows and Linux path spellings. Access is confined to server-fixed roots, with secrets files refused, key-shaped strings redacted, and no delete or move operations.

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.

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

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

Provides a stable, side-effect-free MCP tool contract that enables AI workflows to be prototyped, demoed, tested, or dry-run without connecting to databases, APIs, files, or other real data sources. It enables swapping in a real data server later without changing the AI-facing interface.

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.

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.

Enables natural-language search over locally indexed files such as markdown, text, images, videos, and PDFs, and retrieves indexed text or media metadata by path. It lets Cursor query a local embedding index built with Gemini and SQLite.

Enables agents to perform workspace-scoped file deletion through a ticket-gated workflow: preview paths and risks, move approved files into a recoverable .del batch, then permanently purge them after confirmation.

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

Local-first filesystem MCP bridge with ripgrep search, atomic writes, multiple transports

Enables accessing and managing files from configured folders with filtering and size limits, allowing listing, reading, and searching files via MCP tools and resources.

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