DOCX MCP Server
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Server capabilities have not been inspected yet.
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| extract_textC | Extract plain text content from a DOCX file |
| convert_to_htmlA | Convert DOCX file to HTML with formatting preserved |
| analyze_structureC | Analyze document structure, headings, and formatting elements |
| extract_imagesB | Extract and list images from a DOCX file |
| convert_to_markdownC | Convert DOCX file to Markdown format |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 5 tools
Each tool has a clearly distinct purpose with no overlap: analyze_structure focuses on metadata and formatting, convert_to_html and convert_to_markdown handle different output formats, extract_images targets embedded media, and extract_text retrieves raw content. An agent can easily differentiate between structural analysis, format conversion, and content extraction tasks.
All tool names follow a consistent verb_noun pattern using snake_case (e.g., analyze_structure, convert_to_html, extract_text). The verbs (analyze, convert, extract) are distinct and appropriately descriptive, creating a predictable and readable naming convention throughout the set.
With 5 tools, this server is well-scoped for DOCX file processing. Each tool earns its place by covering essential operations: structural analysis, format conversion to HTML and Markdown, image extraction, and text extraction. This count is neither too thin nor bloated for the domain.
The toolset provides strong coverage for core DOCX processing needs, including analysis, conversion, and extraction. A minor gap exists in editing or modification capabilities (e.g., update_content or merge_documents), but agents can work around this by using the conversion tools to intermediate formats. The surface is largely complete for reading and transforming DOCX files.