codex-mcp-server

🥈Silver

Codex MCP Server enables Claude Code to use Codex's AI capabilities directly. It is a TypeScript wrapper for OpenAI Codex CLI that allows operations teams to automate code generation, refactoring, and debugging tasks. Integrates with Cursor and other MCP-compatible tools.

402320Updated Yesterday

Intermediate30min to implementautomation

Saves ~135 min per use

Quick InstallView Source

git clone https://github.com/tuannvm/codex-mcp-server.git

Works with:

Claude

Overview

About This Skill

How to Use

[{"step":"Install the codex-mcp-server in your Claude Code environment by running: `npm install -g @modelcontextprotocol/server-codex` and configuring your MCP client with the server endpoint.","tip":"Ensure your MCP client (e.g., Cursor, VS Code with MCP extension) is properly configured to communicate with the codex-mcp-server. Test the connection with a simple 'hello world' prompt first."},{"step":"Prepare your code snippet and requirements. Save the code to a file (e.g., `script.py`) or paste it directly into your prompt. Clearly specify the task (generate/refactor/debug) and any constraints (e.g., language version, design patterns).","tip":"For debugging, include the exact error message and stack trace. For refactoring, specify the target architecture (e.g., 'convert to functional programming style')."},{"step":"Execute the prompt through your MCP-compatible tool. For example, in Cursor, use the MCP sidebar to select the codex-mcp-server and paste your prompt.","tip":"If the output is too verbose, ask the server to focus on specific aspects (e.g., 'Only show the refactored function, not the entire file')."},{"step":"Review the generated code and integrate it into your project. Test thoroughly, especially for edge cases introduced by the changes.","tip":"Use the inline comments provided by the server to understand key modifications. Compare the original and refactored code side-by-side if needed."},{"step":"Iterate as needed. If the output doesn’t meet expectations, refine your prompt with more specific requirements or constraints.","tip":"For complex tasks, break them into smaller prompts (e.g., 'First refactor the function, then optimize the algorithm')."}]

Setup & Installation

Quick Install

No install command available. Check the GitHub repository for manual installation instructions.

Alternative Install (Git Clone)

git clone https://github.com/tuannvm/codex-mcp-server

Requirements

Claude Code or compatible AI agent
Works with: Claude

Quick Start Guide

Install the Skill

Copy the install command above and run it in your terminal.

Open Your AI Agent

Launch Claude Code, Cursor, or your preferred AI coding agent.

Try It Out

Use the prompt template or examples below to test the skill.

Customize

Adapt the skill to your specific use case and workflow.

Usage Examples

Prompt Template

Use the codex-mcp-server to [TASK: generate/refactor/debug] the following code snippet: [CODE_SNIPPET]. Apply [SPECIFIC_REQUIREMENTS: e.g., 'Python 3.10+ syntax', 'React best practices', 'OOP design patterns']. Return the updated code with inline comments explaining key changes. If debugging, include the error message: [ERROR_MESSAGE].

Example Output

```python
# Original code (simplified for example):
def calculate_discount(price, discount_percent):
    return price * (1 - discount_percent)

# Refactored code with requirements (Python 3.10+, type hints, validation):
from typing import Union

def calculate_discount(
    price: Union[int, float],
    discount_percent: Union[int, float]
) -> float:
    """
    Calculate the discounted price with input validation.
    
    Args:
        price: Original price (must be positive)
        discount_percent: Discount percentage (0-100)
    
    Returns:
        Discounted price
    
    Raises:
        ValueError: If inputs are invalid
    """
    if not isinstance(price, (int, float)) or price <= 0:
        raise ValueError("Price must be a positive number")
    if not isinstance(discount_percent, (int, float)) or not (0 <= discount_percent <= 100):
        raise ValueError("Discount must be a number between 0 and 100")
    
    return round(price * (1 - discount_percent / 100), 2)

# Key changes:
# 1. Added type hints for better IDE support and maintainability
# 2. Included input validation for robustness
# 3. Normalized discount_percent to 0-100 range
# 4. Added rounding to 2 decimal places for currency
# 5. Included docstring for API documentation
```