codex-mcp-go: Go-based MCP server that serves as a bridge for Codex CLI, enabling various AI coding assistants to seamlessly

Last updated: 2026-02-03 · Indexed by AgentSkillsHub · Auto-synced every 8h

How to install codex-mcp-go

npx @zenfun510/codex-mcp-go
git clone https://github.com/w31r4/codex-mcp-go.git

Taken from the project's README on GitHub.

Security audit verdict: SAFE · quality 66/100

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.

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.

Quick Facts

Stars	51
Forks	5
Language	Go
Category	MCP Server
License	MIT
Quality Score	66/100
Open Issues	3
Last Updated	2026-02-03
Created	2025-11-27
Platforms	claude-code, cli, codex, go, mcp
Est. Tokens	~11k

About codex-mcp-go

codex-mcp-go Codex CLI 的 MCP 协议封装实现 ⭐ 如果觉得好用，请给个 Star 吧！您的支持是我们更新的动力 ⭐ English | 简体中文简介是一个基于 Go 语言实现的 MCP (Model Context Protocol) 服务器。它封装了 OpenAI 的 Codex CLI，使其能够作为 MCP 工具被 KiloCode、Roo Code、Cline 等各种 "Vibe Coding" AI 客户端调用。这个项目的初衷很简单：让强者更强，让专才专用。在我自己的工作流中（在 KiloCode 里使用 Gemini 3.0 Pro），我发现像 Gemini 这样的先进模型拥有强大的规划能力和想象力，但在修复自己生成的复杂代码时偶尔会“卡壳”。而 Codex，这位老练的“代码老师傅”，虽然在宏大叙事上稍逊一筹，但在具体的代码实现、Bug...

Compatible Skills

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

ai-observer — semantic(0.24)+complementary+same_lang+similar_pop+shared_platform (53%)
leash — semantic(0.21)+complementary+same_lang+similar_pop+shared_platform (52%)
subtask — semantic(0.20)+complementary+same_lang+similar_pop+shared_platform (52%)
pockode — semantic(0.19)+complementary+same_lang+similar_pop+shared_platform (52%)

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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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