SecurityRonin/docx-mcp
by Various
MCP server for reading and editing Word (.docx) documents with track changes, comments, footnotes, and structural validation
MCP
SecurityRonin/docx-mcp
Added 1 June 2026
Overview
An MCP (Model Context Protocol) server that reads and edits Word (.docx) documents. It supports track changes, comments, footnotes, and structural validation, enabling AI agents to programmatically modify documents with revision tracking.
Best for
Best for
Developers building AI-assisted document editing pipelines
Use cases
- Automating document review workflows with track changes
- Extracting comments and footnotes from .docx files
- Validating document structure programmatically
How to use
Install
pip install docx-mcp-server Tools exposed
open_documentcreate_documentcreate_from_markdownclose_documentget_document_infosave_documentget_headingssearch_textget_paragraphinsert_textdelete_textreplace_textmodify_celledit_header_footerset_formattingset_track_changesget_tracked_changesaccept_changesreject_changesgenerate_change_summary
Tested with
Claude Desktop, Claude Code, Cursor, Windsurf, VS Code
Notes
An MCP (Model Context Protocol) server that reads and edits Word (.docx) documents. It supports track changes, comments, footnotes, and structural validation, enabling AI agents to programmatically modify documents with revision tracking.
19 stars on GitHub. Last updated 2026-05-28. Licensed MIT.
Use cases
- Automating document review workflows with track changes
- Extracting comments and footnotes from .docx files
- Validating document structure programmatically
Pros
- Handles track changes and comments, unlike basic document readers
- Provides structural validation for .docx files
- Python-based and easy to integrate with existing MCP workflows
Cons
- Small community and limited adoption (19 GitHub stars)
- Requires an MCP-compatible AI client to function
- Only supports the .docx format, not older .doc
Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.
Pros
- Handles track changes and comments, unlike basic document readers
- Provides structural validation for .docx files
- Python-based and easy to integrate with existing MCP workflows
Cons
- Small community and limited adoption (19 GitHub stars)
- Requires an MCP-compatible AI client to function
- Only supports the .docx format, not older .doc
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