HermesOffice: Free, open-source AI Office suite (Word, Excel, PowerPoint, PDF, Markdown) — macOS build, one-click install

by criptogus · MCP Server · ★ 624

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

Security audit verdict: SAFE · quality 65/100

Flagged: sudo usage. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →

The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.

agentai-nativedocxelectronhermeslocal-firstmcpoffice-suiteopen-sourcepdf

Quick Facts

Stars624
Forks83
LanguageTypeScript
CategoryMCP Server
LicenseApache-2.0
Quality Score65/100
Open Issues23
Last Updated2026-11-03
Created2026-08-04
Platformscli, mcp, node
Est. Tokens~18k

About HermesOffice

HermesOffice The world's first full-featured open-source AI Office suite. Website · Download · Privacy · Demo HermesOffice is a free, open-source alternative to Microsoft Office for macOS, Windows, and Linux, built around AI editing as a first-class workflow rather than a bolted-on chat box.

Compatible Skills

These tools work well together with HermesOffice for enhanced workflows:

  • openocta — semantic(0.28)+complementary+same_lang+similar_pop+shared_platform (60%)
  • wesight — semantic(0.20)+complementary+same_lang+similar_pop+shared_platform (57%)
  • Wegent — semantic(0.17)+complementary+same_lang+similar_pop+shared_platform (56%)
  • opencode-parser — semantic(0.20)+complementary+rare_topics+same_lang+shared_platform (56%)
  • kordoc — semantic(0.34)+rare_topics+same_lang+similar_pop+shared_platform (56%)

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How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. 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:

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