Office-Word-MCP-Server

Creates new Word documents and manages their complete lifecycle (creation, retrieval, copying, conversion) through the Model Context Protocol interface. Implements MCP tool registration to expose document operations as standardized callable functions that AI assistants can invoke, with python-docx as the underlying document manipulation library. The server coordinates between MCP protocol handlers and document tool modules, enabling stateless document operations across multiple AI assistant sessions.

Inserts diverse content elements (headings at multiple levels, paragraphs, tables, images, page breaks, footnotes) into Word documents with precise positioning and styling control. Uses python-docx's document object model to append elements to the document body in sequence, supporting style application at insertion time. The capability maintains document structure through heading hierarchy levels (1-9) and enables table creation with custom row/column data, image embedding with scaling parameters, and footnote/endnote insertion with automatic numbering.

Inserts footnotes and endnotes into documents with automatic numbering and positioning. Uses python-docx's footnote/endnote API to add notes at the document level with automatic reference markers and numbering. Footnotes appear at the bottom of pages, endnotes at document end. The capability handles automatic numbering sequencing and maintains note references throughout the document.

Applies formatting to text ranges within documents including bold, italic, underline, font color, font family, and font size modifications. Works by identifying text ranges within paragraphs and applying formatting properties through python-docx's run-level formatting API. Supports both direct formatting (character-level properties) and style-based formatting (applying named Word styles to paragraphs). Includes search-and-replace functionality that locates text patterns and applies formatting to matched ranges.

Creates tables with custom dimensions and data, then applies formatting including borders, cell shading, header row styling, and cell alignment. Uses python-docx's table insertion API to create rectangular table structures, then iterates through cells to apply formatting properties. Supports header row designation with automatic styling and cell-level background color (shading) application. Border formatting applies to entire tables with style and width customization.

Implements document-level password protection using the msoffcrypto-tool library to encrypt Word documents with user-specified passwords. The protection mechanism encrypts the entire .docx file (which is a ZIP archive) using Office Open XML encryption standards. When a protected document is opened, users must provide the password to decrypt and access content. The capability integrates with the document lifecycle, allowing protection to be applied after content creation.

Extracts and displays document metadata including title, author, subject, keywords, creation date, and modification date. Uses python-docx's core properties API to read document metadata from the .docx file's internal XML structure. Enables AI systems to inspect document properties before processing and potentially modify metadata during document creation. Metadata is stored in the document's core.xml file within the .docx ZIP archive.

Extracts complete text content from Word documents while preserving paragraph structure and basic formatting information. Iterates through document elements (paragraphs, tables, sections) and concatenates text with structural markers (newlines between paragraphs, table delimiters). Returns both raw text and structured representation with element types and formatting metadata. Enables AI systems to read and analyze document content for processing, summarization, or modification.

Lists available Word documents in a configured directory or searches for documents matching specific criteria (filename patterns, date ranges, size filters). Scans the filesystem for .docx files and returns metadata including filename, file path, file size, and modification date. Enables AI systems to discover and select documents for processing without requiring explicit file paths. Supports filtering and sorting operations on discovered documents.

Creates a copy of an existing Word document at a new location with optional filename modification. Uses filesystem copy operations to duplicate the .docx file, preserving all content, formatting, and metadata. Enables AI systems to create document variants or backups without modifying the original. Supports both same-directory copies (with renamed filename) and cross-directory copies.

Converts Word documents (.docx) to PDF format using the docx2pdf library, which wraps LibreOffice/OpenOffice conversion engines. The conversion process loads the .docx file, renders it through the Office engine, and outputs a PDF file with preserved formatting, fonts, and layout. Enables AI systems to generate PDF versions of documents for distribution, archival, or format-specific requirements.