openai-codex-mcp

Name: openai-codex-mcp
Author: agency-ai-solutions

@agency-ai-solutions

Repository

About openai-codex-mcp

An MCP server to communicated with, use, and wrap the API for the OpenAI Codex CLI tool.

#openai-codex #mcp-server #api-wrapper

Basic information

Config

Add this server to your MCP-compatible client using the configuration below.

{
  "mcpServers": {
    "openai-codex-mcp": {
      "command": "uv",
      "args": [
        "venv",
        "#",
        "creates",
        "a",
        ".venv/",
        "directory"
      ]
    }
  }
}

Tools

No tools detected

We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.

Overview

What is openai-codex-mcp?

openai-codex-mcp is a JSON-RPC server that wraps the OpenAI Codex CLI tool, enabling Claude Code to use OpenAI’s models for code generation, explanation, and debugging within the same interface.

How to use openai-codex-mcp?

Install with uv pip install . after creating a venv, then run codex_server (or uvicorn codex_server:app). Register it in Claude Code via claude mcp add /path/to/openai_codex_mcp.json or manually with base URL http://localhost:8000/ and protocol JSON-RPC 2.0. No authentication needed.

Key features of openai-codex-mcp

Specialized methods: write_code, explain_code, debug_code
Supports multiple OpenAI models (O‑series and GPT)
Simplified parameter naming for easy integration
Runs as a lightweight, standalone Python server
No authentication required for the MCP server itself

Use cases of openai-codex-mcp

Generate code in a specific language for a given task
Obtain detailed explanations of how code works
Find and fix bugs in problematic code
Leverage different OpenAI models (o4‑mini, gpt‑4o, etc.) for specialized tasks

FAQ from openai-codex-mcp

What makes this MCP server different from directly using the Codex CLI?

It provides a JSON-RPC interface specifically designed for Claude Code, with dedicated methods for common coding tasks and simplified parameter naming.

What are the runtime requirements?

Python 3.12+, the OpenAI Codex CLI tool (installed via npm install -g @openai/codex), and a valid OpenAI API key configured for the Codex CLI.

Where does the code/data processed by the server live?

The README does not specify data storage; all processing occurs locally via the Codex CLI and the MCP server on localhost.

Does the server support authentication?

No – the base URL configuration does not require an authentication token.

What transport protocol does it use?

JSON-RPC 2.0 over HTTP, listening on port 8000 by default.

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