scrivener-mcp: The definitive MCP server for Scrivener — connect your novels, screenplays, and manuscripts to Claude, ChatGPT

by writerslogic · MCP Server · ★ 69

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

How to install scrivener-mcp

npm install -g scrivener-mcp
npx -y @smithery/cli install scrivener-mcp --client claude

Taken from the project's README on GitHub. Check the security audit before running it.

Security audit verdict: SAFE · quality 70/100

None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. 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.

ai-writingchatgptclaudecontent-analysiscopilotcreative-writingcursormanuscriptmcpmcp-server

Quick Facts

Stars69
Forks23
LanguageTypeScript
CategoryMCP Server
LicenseAGPL-3.0
Quality Score70/100
Open Issues7
Last Updated2026-10-25
Created2025-09-03
Platformsclaude-code, mcp, node
Est. Tokens~17k

About scrivener-mcp

Scrivener MCP Connect your Scrivener projects to Claude, ChatGPT, and other AI assistants Install · What You Can Do · All Tools · Guides · Contributing Scrivener MCP lets your AI assistant open, read, edit, analyz

Compatible Skills

These tools work well together with scrivener-mcp for enhanced workflows:

  • whoop-mcp — semantic(0.32)+rare_topics+same_lang+similar_pop+shared_platform (51%)
  • square-mcp-server — semantic(0.43)+same_lang+similar_pop+shared_platform (50%)

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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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