Word MCP Server

The Word MCP Server is a Python‑based Model Context Protocol service that exposes a rich set of tools for creating, editing, and formatting Microsoft Word (.docx) documents through natural language commands. By integrating with an LLM, developers can let the assistant “talk” to Word—adding headings, paragraphs, tables, images, and even styled runs of text—without writing any document‑generation code themselves. This lowers the barrier to generating polished reports, proposals, or academic papers directly from conversational prompts.

At its core, the server translates MCP tool calls into operations. When an LLM issues a request such as “create a new document with a title and table of contents,” the server spawns a fresh Word file, inserts the requested headings, and populates the outline. The same API surface is used for more advanced edits: inserting images from disk or a NumPy array, customizing font size, weight, color, and paragraph alignment, or adding highlighted text. These capabilities are exposed as declarative tools that the LLM can invoke by name, making it straightforward to compose complex documents through a sequence of high‑level actions.

Key features include:

• Document lifecycle management – create, open, and save Word files programmatically.
• Text manipulation – add headings of arbitrary levels, paragraphs with optional styling, and runs with bold, italics, color, or highlight.
• Media insertion – embed pictures from file paths or in‑memory image arrays, with width control.
• Table creation – build tables of arbitrary size and style, then populate cells directly.
• Resource handling – store reusable prompts and templates in dedicated folders for quick access.

Real‑world use cases span automated report generation for business analytics, dynamic content creation in educational platforms, or generating legal documents from structured data. For example, a data‑science team can feed the LLM a dataset summary and ask it to “produce a Word report with charts, tables, and a conclusion.” The MCP server handles all the document formatting while the LLM focuses on content logic.

Integration into existing AI workflows is seamless: developers configure the server in a JSON file, launch it via FastMCP, and then reference its tool set from any LLM that supports MCP. Because the server runs as a separate process, it can be scaled independently, secured behind authentication layers, or orchestrated with other document‑centric services. Its straightforward API and reliance on the well‑established library make it a dependable choice for teams that need to automate Word document creation without reinventing the wheel.