No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by ykarapazar · MCP Server · ★ 180
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is word-mcp-live safe to install? View the security audit →
word-mcp-live The only MCP server that edits Word documents while they're open · · · · []() word-mcp-live gives any AI assistant that supports MCP full control of Microsoft Word. Open a document, tell the AI what you need, and watch it happen — formatting, tracked changes, comments, and all. Changes appear live in your open document. Without word-mcp-live AI can discuss your document but can't touch it You copy-paste between AI and Word, losing formatting Track changes? You do those manually after the fact Every edit means save → close → process → reopen With word-mcp-live "Add a tracked change replacing ABC Corp with XYZ Ltd" — done Changes a
| Stars | 180 |
| Forks | 32 |
| Language | Python |
| Category | MCP Server |
| License | MIT |
| Quality Score | 76.619836581756/100 |
| Open Issues | 16 |
| Last Updated | 2026-05-29 |
| Created | 2026-02-12 |
| Platforms | claude-code, mcp, python |
| Est. Tokens | ~32k |
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word-mcp-live is The only MCP server that edits Word documents while they're open — 114 tools, live editing, tracked changes, per-action undo. It is categorized as a MCP Server with 180 GitHub stars.
word-mcp-live is primarily written in Python. It covers topics such as ai, claude, com-automation.
You can find installation instructions and usage details in the word-mcp-live GitHub repository at github.com/ykarapazar/word-mcp-live. The project has 180 stars and 32 forks, indicating an active community.
word-mcp-live is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to word-mcp-live on Agent Skills Hub include vscode-mcp, youtube-connector-mcp, Overture. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. It is a first-layer scan, not a manual audit — we say so rather than overstate it.
The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.
Sources & who's responsible: