Creating a coding agent that can write and run code automatically might sound like sci-fi, but with n8n—an extendable workflow automation tool—it’s entirely possible. Whether you're a developer looking for a productivity boost or a business user trying to automate tech support tasks, an n8n coding agent can revolutionize your workflow. In this guide, we’ll walk you through how to build a no-code/low-code agent in n8n that generates, executes, and even debugs code, all autonomously.
What Is an n8n Coding Agent?
An n8n coding agent is a workflow or bot created using n8n that leverages AI models (like OpenAI or Ollama) to write code based on user prompts, executes it in a safe environment, and returns results—all in an automated loop.
Think of it as having your own AI-powered junior developer available 24/7, ready to generate small code snippets, validate logic, or help debug issues automatically.
Why Build One?
- Automated Coding Tasks — Generate and run boilerplate code on demand.
- AI Debugging Assistant — Spot and correct syntax or runtime errors dynamically.
- DevOps Support — Auto-generate Dockerfiles, shell scripts, or API calls.
- Learning Tool — Quickly test Python or JavaScript snippets.
Tools You’ll Need
Before you start, make sure you have the following in place:
- A working self-hosted or cloud-hosted instance of n8n
- API key for OpenAI or a self-hosted LLM model like Ollama
- Access to your local system’s code execution environment (e.g., Docker, Node.js, or Python runtime)
- (Optional) Code sandboxing, such as using Docker-in-Docker or isolated containers
Step-by-Step: Building an n8n Coding Agent
Step 1: Set Up Your n8n Environment
If you haven’t installed n8n yet, check out this detailed self-hosted n8n setup guide or use Docker to get up and running in under five minutes.
For security and speed reasons, self-hosting is recommended when working with code execution agents.
Step 2: Create a New Workflow in n8n
- Log in to your n8n editor UI.
- Click on “Workflows” and create a new one.
- Name it something like “AI Coding Agent”.
You’ll start with a Webhook or Trigger node to initiate your coding request.
Step 3: Add a Prompt Input Node
- Use either a
Webhook,Google Sheets, orTelegramnode as your trigger input. - Format it to accept inputs like:
- Programming language
- Desired functionality (e.g., “create a calculator in Python”)
Use a node like Set to format the incoming data into a prompt for the AI.
Step 4: Send the Prompt to an LLM
Add an HTTP Request node to call OpenAI (or use a community package for Ollama).
Configure:
- URL:
https://api.openai.com/v1/chat/completions - Method:
POST - Headers: Authorization with your OpenAI API key
- JSON Body:
{ "model": "gpt-4", "messages": [ { "role": "system", "content": "You’re a helpful code assistant." }, { "role": "user", "content": "Write a Python script to sort an array using quicksort." } ] }
Parse the response to extract the code block using a Set or Function node.
💡 Tip: Add a
Markdown Extractorfunction to isolate code from AI-generated markdown responses.
Step 5: Run the Code Using the Code Node
The heart of this n8n coding agent lies in the Code node.
- Choose the language (JavaScript or Python if enabled)
- Dynamically insert the code from the previous output
- Wrap it in a try-catch block to capture errors
Example JavaScript structure:
try {
const result = eval($json["code"]);
return [{ result }];
} catch (err) {
return [{ error: err.message }];
}
If you're executing non-JS code (like Python), you can call a shell command using an Execute Command node or trigger a Docker container safely.
Step 6: Return the Output to User
Use a Respond to Webhook, Telegram, or Email node to deliver the result back.
Include both:
- The original prompt
- The AI-generated code
- The execution result or error message
Step 7: Add Error Handling and Retries
Implement catch paths with a separate error handler. Consider following best practices outlined in this error handling in n8n guide to retry failed requests or alert you on failure.
Example Workflow Use Case: Build a REST API with One Prompt
Input Prompt: "Generate a basic Express.js REST API with a single GET endpoint at /status that returns 'OK'."
Output:
AI generates the Express code →
const express = require("express");
const app = express();
app.get("/status", (req, res) => res.send("OK"));
app.listen(3000, () => console.log("API running"));
n8n runs the code inside a Docker container and tests if curl http://localhost:3000/status returns "OK".
You can extend the workflow to deploy this API on your local server or VM.
Optional Enhancements
- Authentication Node: Add a token or API key validator for secure inputs.
- Version Control: Push generated code to GitHub using the
HTTP Requestnode. - Unit Testing: Auto-generate unit tests from the prompt or using additional AI calls.
Table: Components of an n8n Coding Agent
Here's a quick breakdown of essential components and their purpose:
| Component | Node Type | Function |
|---|---|---|
| Trigger Input | Webhook, Sheet, etc. | Starts the request |
| Prompt Prep | Set / Function | Formats input for LLM |
| AI Response | HTTP Request | Gets code from OpenAI or Ollama |
| Code Execution | Code or Exec Command | Runs the returned code |
| Output Handling | Respond Node | Returns result or error |
| Error Reporting | Catch/Error Node | Catches issues and retries or alerts |
Best Practices and Security Tips
- Always validate and sanitize AI-generated code before execution.
- Use isolated containers when executing untrusted code (preferably with Docker).
- Disable OS-level commands that could compromise file systems.
- Limit the types of code that can be run based on language or prompt filters.
If you're running GPT-style models locally, check our guide on fixing the Ollama fetch error to avoid connection issues between n8n and Ollama.
FAQ
How secure is it to run AI-generated code in n8n?
Running unvalidated code can be dangerous. Always sandbox AI-generated code in a secure environment like Docker, and avoid giving write access to your host system.
Can the n8n coding agent work with Python?
Absolutely. While n8n natively supports JavaScript in the Code node, you can use the Execute Command node to run Python scripts on your server.
Do I need a Pro subscription to use AI in n8n?
No. You can use API-based AI services or local models inside your free self-hosted n8n setup. Learn how in How to Use n8n Without Paying a Dime.
Which AI models can I use with this?
You can use OpenAI (GPT-3.5, GPT-4), Ollama, or even a combination through services like LangChain or CrewAI. Depending on your workflow complexity, either will work well.
Is this better than just using ChatGPT?
With n8n, you don't just generate code—you immediately run it, validate it, and integrate it into larger workflows, making it much more powerful than standalone ChatGPT interactions.
With just a few nodes, you can create a powerful n8n coding agent that not only assists with code generation but actually becomes your automation-powered code executor. Perfect for those running developer workflows, learning environments, or even automating code tasks at scale.
Ready to build your own? Get started with n8n's free automation platform and harness the power of AI + automation today.