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 airmang · MCP Server · ★ 65
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is hwpx-mcp-server safe to install? View the security audit →
📄 hwpx-mcp-server AI 에이전트가 HWPX 문서를 바로 읽고, 찾고, 수정하게 만드는 MCP 서버 한글 워드프로세서 없이 · 순수 파이썬 · 크로스 플랫폼 🧩 HWPX Stack (3종) hwpx-mcp-server는 모델 컨텍스트 프로토콜(MCP) 표준을 따르는 서버로, python-hwpx 기반에서 HWPX 문서의 열람 ·
| Stars | 65 |
| Forks | 22 |
| Language | Python |
| Category | MCP Server |
| License | Apache-2.0 |
| Quality Score | 67.46716835297/100 |
| Open Issues | 10 |
| Last Updated | 2026-07-27 |
| Created | 2025-09-19 |
| Platforms | claude-code, mcp, python, vscode |
| Est. Tokens | ~18k |
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hwpx-mcp-server is MCP server for AI agents to read, edit, inspect, and validate local HWPX documents.. It is categorized as a MCP Server with 65 GitHub stars.
hwpx-mcp-server is primarily written in Python. It covers topics such as ai-agent, claude-desktop, document-automation.
You can find installation instructions and usage details in the hwpx-mcp-server GitHub repository at github.com/airmang/hwpx-mcp-server. The project has 65 stars and 22 forks, indicating an active community.
hwpx-mcp-server is released under the Apache-2.0 license, making it free to use and modify according to the license terms.
The top alternatives to hwpx-mcp-server on Agent Skills Hub include omega-memory, utcp-mcp, notion-mcp-server. 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: