Documentation

ProDex Node for Self-Hosted n8n

Community node package that runs OpenAI Codex inside self-hosted n8n workflows using your ChatGPT/Codex subscription (device-code auth), not pay-per-token API billing.

Features

  • ProDex root node (prompt in, agent result out)
  • ProDex Chat Model for n8n AI Agent (connect to Chat Model input)
  • ProDex Setup node for browser login and credential export inside n8n
  • Token refresh at runtime when access tokens expire
  • Automatic Codex data directory under n8n's own user folder (no manual env vars)
  • Thread modes: new, continue, resume
  • Skills system — install SKILL.md files and reference them in system prompts (static + dynamic)

Developer

Questions, bugs, and feature requests: collegeitpro@gmail.com

  • Sandbox controls and optional structured JSON output

Important caveat

This package uses Codex through the official @openai/codex-sdk, which spawns the Codex CLI and authenticates with ChatGPT subscription tokens. Codex backend endpoints may change without notice. Pin package versions in production.

Requirements

  • Self-hosted n8n (not n8n Cloud)
  • Node.js 18+
  • @openai/codex CLI binaries (installed automatically as a dependency on supported platforms)

Installation

Option A: Install from npm (community node UI)

In self-hosted n8n:

  1. Open Settings → Community Nodes
  2. Click Install
  3. Enter package name:
n8n-nodes-prodex
  1. Accept the risk prompt and install
  2. Restart n8n if prompted

Option B: Custom extensions directory (development)

git clone <this-repo>
cd n8n-nodes-prodex
npm install
npm run build

export N8N_CUSTOM_EXTENSIONS="/absolute/path/to/n8n-nodes-prodex"
n8n start

The package directory must contain installed dependencies (@openai/codex, @openai/codex-sdk). Running npm install in the package folder satisfies that requirement.

For Docker, mount the built package and set N8N_CUSTOM_EXTENSIONS. See docker/Dockerfile.n8n-codex.

Authentication (entirely inside n8n)

No CLI or manual environment variables are required for users.

Step 1: Start device login

  1. Create a workflow with Manual Trigger → ProDex Setup
  2. Set operation to Start Device Login
  3. Execute the workflow
  4. Open the returned verificationUrl and enter userCode in your browser
  5. Sign in with your ChatGPT account

Step 2: Wait for login complete

  1. Change the setup node operation to Wait for Login Complete
  2. Execute again after browser login completes
  3. Confirm the output shows hasCompleteAuth: true

Step 3: Run Codex

Add the ProDex node and run your workflow. Do not select credentials — leave Use n8n Credentials off. Auth is read automatically from auth.json on disk.

If tokens expire and refresh fails, repeat the setup flow with ProDex Setup.

Optional: store tokens in n8n Credentials

Only needed if you prefer n8n Credentials over disk auth (e.g. multi-worker setups):

  1. ProDex Setup → Export Credential Values
  2. Create Credentials → ProDex Auth API and paste the returned fields
  3. On the ProDex node, enable Use n8n Credentials and select that credential
Credential field JSON field from setup node
Access Token accessToken
Refresh Token refreshToken
ID Token idToken
Account ID accountId
Expires At expiresAt

Use with n8n AI Agent (Chat Model)

Connect ProDex Chat Model to the Chat Model input on the AI Agent node:

  1. Complete setup (Start Device Login → Wait for Login Complete)
  2. Add When chat message received (or any trigger) → AI Agent
  3. Add ProDex Chat Model as a separate node on the canvas
  4. Connect ProDex Chat Model → Model to AI Agent → Chat Model
  5. Execute and chat

Example layout:

When chat message received → AI Agent
ProDex Chat Model ──────→ Chat Model (on AI Agent)

Notes:

  • Credentials are optional when auth.json is already on the server
  • Tool nodes connected to AI Agent have limited support — Codex returns text responses, not native LangChain tool-call payloads. For full coding-agent behavior (sandbox, shell, multi-file edits), use the standalone ProDex node
  • Default sandbox is Read Only for safer chat use

Skills (install + system prompt)

Skills are stored as SKILL.md files under {codexHome}/skills/{skill-name}/ (Cursor/Codex-compatible format).

Install a skill

  1. ProDex Setup → Install Skill
  2. Set Skill Name (e.g. release-notes)
  3. Paste full Skill Markdown (YAML frontmatter + body)
  4. Execute

List installed skills

ProDex Setup → List Installed Skills — returns skillNames you can copy into the ProDex node.

Use skills in ProDex

Field Purpose
System Prompt Static instructions on every run
Static Skills Comma/newline skill names always loaded (e.g. release-notes, lint-fix)
Dynamic Skills Expression per item — default ={{ $json.skillNames || $json.skills }}

Dynamic skills accept:

  • Skill names: "release-notes" or ["a", "b"]
  • Inline markdown: full SKILL.md text for one-off runs
  • Objects: [{ "name": "temp", "content": "..." }]

Output includes appliedSkills so you can verify what was loaded.

Usage

  1. Add ProDex to your workflow
  2. Select your ProDex Auth API credential
  3. Set prompt (default expression reads chatInput, prompt, or text)
  4. Choose model, reasoning effort, sandbox, and thread mode
  5. Execute

Output fields

{
  "output": "Agent final response",
  "threadId": "thread_...",
  "items": [],
  "usage": { "inputTokens": 0, "outputTokens": 0, "totalTokens": 0 },
  "model": "gpt-5.4",
  "finishReason": "stop"
}

Thread modes

  • New Thread: starts fresh each run
  • Continue Previous Thread: reuses threadId stored in node static data
  • Resume Thread By ID: resumes explicit thread ID (Codex sessions under the n8n-managed Codex home directory)

Manual E2E test

  1. Install the node on a self-hosted n8n instance
  2. Run ProDex Setup → Start Device Login, complete browser auth, then Export Credential Values
  3. Create the ProDex Auth API credential from the exported JSON
  4. Build workflow: Manual Trigger → ProDex → Set
  5. Prompt: Reply with the single word OK.
  6. Model: gpt-5.4, Sandbox: Read Only, Thread Mode: New Thread
  7. Execute and verify output contains OK and threadId is populated

Development

npm install
npm run build
npm test
npm run lint

Docker example

Build a custom n8n image with Codex preinstalled:

docker build -f docker/Dockerfile.n8n-codex -t n8n-codex .
docker run -p 5678:5678 -e N8N_CUSTOM_EXTENSIONS=/custom-nodes n8n-codex

Codex runtime files are stored automatically under n8n's user folder (for example /home/node/.n8n/codex in the official Docker image).

Security notes

  • Treat credential tokens like passwords
  • Prefer read_only sandbox on shared servers
  • Do not set OPENAI_API_KEY in n8n if you want subscription billing; it can override ChatGPT auth in some Codex versions

License

MIT

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