codex-buddy-for-claude

codex-buddy-for-claude

Enables Claude Code to leverage OpenAI models for expert code review, deep architecture analysis, and security audits, with automatic markdown report generation.

Category
访问服务器

README

codex-buddy-for-claude

MCP server that gives Claude Code access to OpenAI models for:

  • Code Review (codex_review) — expert code review with severity ratings and actionable fixes
  • Deep Thinking (codex_thinkdeep) — architecture decisions, trade-off analysis, debugging hypotheses
  • Security Audit (codex_secaudit) — OWASP-aligned security audit with threat-level-aware analysis

Reports are automatically saved as markdown files to <project>/codex-reports/.

Requirements

Install

# Clone the repo
git clone https://github.com/leo919cc/codex-buddy-for-claude.git
cd codex-buddy-for-claude

# Create venv and install dependencies
python3 -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt

Add to Claude Code

Add the server to your Claude Code MCP config (~/.claude.json):

{
  "mcpServers": {
    "codexreview": {
      "command": "/absolute/path/to/codex-buddy-for-claude/.venv/bin/python",
      "args": ["/absolute/path/to/codex-buddy-for-claude/server.py"]
    }
  }
}

Replace /absolute/path/to/ with the actual path where you cloned the repo.

Then restart Claude Code. You should see the three tools available:

  • mcp__codexreview__codex_review
  • mcp__codexreview__codex_thinkdeep
  • mcp__codexreview__codex_secaudit

Authentication

The server supports two auth methods. It prefers OAuth (free with subscription) and falls back to API key (pay-per-token).

Option A: ChatGPT subscription (recommended)

Use your ChatGPT Plus ($20/mo) or Pro ($200/mo) subscription — no per-token API costs.

# Install Codex CLI and login (one-time)
npm install -g @openai/codex
codex login

This saves OAuth tokens to ~/.codex/auth.json. The MCP server auto-detects them on startup. The report footer will show (subscription) to confirm.

Option B: API key (pay-per-token)

Create a .env file in the repo directory:

echo "OPENAI_API_KEY=sk-your-key-here" > .env

Or export it in your shell:

export OPENAI_API_KEY=sk-your-key-here

The report footer will show (API) when using this method.

Both configured?

If both OAuth and API key are available, OAuth is used by default (free). The API key serves as fallback if OAuth tokens expire or fail.

Configuration

Env Variable Default Description
OPENAI_API_KEY (optional if using OAuth) Your OpenAI API key
CODEX_MODEL gpt-5.4 Default model for all tools

You can also override the model per-call by passing the model parameter to any tool.

Supported models

Any OpenAI model works. High-reasoning models (codex/5.x series) automatically use the Responses API:

  • gpt-5.4 (default) — high reasoning
  • gpt-5.4-pro — xhigh reasoning (premium pricing)
  • gpt-5.3-codex, gpt-5.2-codex, gpt-5.1-codex, etc.
  • gpt-4o, gpt-4-turbo, etc. — use standard chat completions API

Usage

Once configured, Claude Code will automatically have access to the tools. You can ask Claude to:

  • "Review this file" → triggers codex_review
  • "Think deeply about whether we should use X or Y" → triggers codex_thinkdeep
  • "Run a security audit on this file" → triggers codex_secaudit

Parameters

All tools accept:

  • model — override the default model
  • project_dir — where to save reports (auto-detected from file paths if not set)

codex_review

  • files (required) — list of absolute file paths
  • context — what the code does, focus areas

codex_thinkdeep

  • problem (required) — the question or decision to analyze
  • context — constraints, what you've considered
  • files — relevant code files for grounding

codex_secaudit

  • files (required) — list of absolute file paths
  • context — deployment context, threat model
  • threat_levellow | medium | high | critical

License

MIT

推荐服务器

Baidu Map

Baidu Map

百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。

官方
精选
JavaScript
Playwright MCP Server

Playwright MCP Server

一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。

官方
精选
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。

官方
精选
本地
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。

官方
精选
本地
TypeScript
VeyraX

VeyraX

一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。

官方
精选
本地
graphlit-mcp-server

graphlit-mcp-server

模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。

官方
精选
TypeScript
Kagi MCP Server

Kagi MCP Server

一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。

官方
精选
Python
e2b-mcp-server

e2b-mcp-server

使用 MCP 通过 e2b 运行代码。

官方
精选
Neon MCP Server

Neon MCP Server

用于与 Neon 管理 API 和数据库交互的 MCP 服务器

官方
精选
Exa MCP Server

Exa MCP Server

模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。

官方
精选