fennara-godot-ai: AI chat and agent tooling for Godot, with both MCP support and in-built native chat window

by fennaraOfficial · MCP Server · ★ 312

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

Security audit verdict: SAFE · quality 73/100

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-agentai-codingai-game-developmentclaude-codecodexcursorgamedevgdscriptgodotgodot-4

Quick Facts

Stars312
Forks15
LanguageRust
CategoryMCP Server
LicenseMIT
Quality Score73/100
Open Issues9
Last Updated2026-10-24
Created2026-06-01
Platformsclaude-code, codex, mcp, rust
Est. Tokens~24k

About fennara-godot-ai

Fennara Godot AI English · 简体中文 · Español · Português do Brasil · 日本語 · 한국어 · Русский · Français · Deutsch · Türkçe Used by Godot developers and teams, including Somni Game Studios. Fennara gives AI assistants a live connection to Godot. Use it from MCP-capable apps like Codex, Claude, Cursor, Gemini, and Antigravity, or from the optional in-editor chat dock.

Compatible Skills

These tools work well together with fennara-godot-ai for enhanced workflows:

  • GodotPrompter — semantic(0.63)+complementary+rare_topics+shared_platform (67%)
  • godot-mcp — semantic(0.75)+rare_topics+similar_pop+shared_platform (65%)
  • Godot-MCP — semantic(0.75)+rare_topics+similar_pop+shared_platform (64%)

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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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