# OpenAI Codex Setup

[OpenAI Codex](https://openai.com/blog/openai-codex) is OpenAI's terminal-first workspace that pairs a shell, editor, and conversational developer agent. With Model Context Protocol (MCP) support, you can connect Codex directly to Umbraco's tools and data so the assistant can work inside your projects.

{% hint style="info" %}
The examples below use the Developer MCP package (`@umbraco-cms/mcp-dev`). Replace the package name if you are using a different Umbraco MCP server.
{% endhint %}

## Getting started

Option A: Install via npm:

```bash
npm install -g @openai/codex
```

Option B: Install via Homebrew:

```bash
brew install codex
```

### Configure using the Codex CLI

1. Add the Umbraco MCP server with the Codex CLI:

```bash
codex mcp add umbraco-mcp -- npx -y @umbraco-cms/mcp-dev@latest
```

2. Define configuration values directly. If you prefer to keep secrets in your shell session, pass them as environment variables during registration:

```bash
codex mcp add umbraco-mcp \
  --env UMBRACO_CLIENT_ID="your-id" \
  --env UMBRACO_CLIENT_SECRET="your-secret" \
  --env UMBRACO_BASE_URL="https://your-domain.com" \
  --env NODE_TLS_REJECT_UNAUTHORIZED="0" \
  --env UMBRACO_INCLUDE_TOOL_COLLECTIONS="document,media,document-type,data-type" \
  -- npx -y @umbraco-cms/mcp-dev@latest
```

Replace the following values with your local connection details:

* `UMBRACO_CLIENT_ID`
* `UMBRACO_CLIENT_SECRET`
* `UMBRACO_BASE_URL`
* `UMBRACO_INCLUDE_TOOL_COLLECTIONS`

This command stores the MCP server as `umbraco-mcp` in your Codex configuration file (typically `~/.codex/config.toml`).

3. Use the command below to see which MCP servers Codex is currently loading:

```cs
codex mcp list
```

## Managing tools and tool collections

When you need to change the tool set:

* Update your `.env` file with the tool collections you want (for example, `document,media`).
* Run the `codex mcp list` command to confirm that the server is healthy.


---

# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://docs.umbraco.com/umbraco-in-ai/mcp/local-mcp-setup/openai-codex.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.