# Build & deploy MVPs from text prompts with GitHub and Vercel: n8n workflow

> Started by someone opening a chat with it, and works across GitHub. It puts OpenAI behind a retrieval step, so answers are drawn from documents you supply...

Source: https://millionrounds.com/workflow/build-and-deploy-mvps-from-text-prompts-with-github-and-verc (Millionrounds; every figure on the page links to its filing or article)

[Automation library](https://millionrounds.com/workflows) · [AI assistants](https://millionrounds.com/workflows?category=AI+assistants#library)

# Build & deploy MVPs from text prompts with GitHub and Vercel

Started by someone opening a chat with it, and works across GitHub. It puts OpenAI behind a retrieval step, so answers are drawn from documents you supply rather than from the model alone. 52 steps, 3 branches, 3 loops or waits: large, and worth reading before you trust it with anything live.

Large Calls a model: OpenAI Retrieval

[Download free](https://millionrounds.com/login?next=%2Fapp%2Fworkflow%2Fbuild-and-deploy-mvps-from-text-prompts-with-github-and-verc)

**52 steps** Large: read it before trusting it with anything live

**3** Branches: places the flow splits

**3** Loops or waits

**1** Service it connects to

## The flow

Starts it 5 Model 12 Logic 22 Service 13

The steps in the order they run, from what starts it.

- 1 **When chat message received** Chat trigger *Starts it*
- 2 **OpenAI Chat Model** Lm Chat Open Ai *Model*
- 3 **Window Buffer Memory** Memory Buffer Window *Model*
- 4 **create_mvp** Tool Workflow *Model*
- 5 **create_mvp trigger** Execute Workflow trigger *Starts it*
- 6 **When clicking ‘Test workflow’** Manual trigger *Starts it*
- 7 **test input** Code *Logic*
- 8 **OpenAI Chat Model1** Lm Chat Open Ai *Model*
- 9 **Structured Output Code** Output Parser Structured *Model*
- 10 **get_file** Github Tool *Service*
- 11 **HTTP Request1** Http Request *Service*
- 12 **get_image** Tool Http Request *Model*
- 13 **Code** Code *Logic*
- 14 **OpenAI Chat Model2** Lm Chat Open Ai *Model*
- 15 **Code2** Code *Logic*
- 16 **OpenAI Chat Model3** Lm Chat Open Ai *Model*
- 17 **Fetch Latest Deployment** Http Request *Service*
- 18 **Chat Agent** Agent *Model*
- 19 **Parse Input** Code *Logic*
- 20 **Code3** Code *Logic*
- 21 **test pos-creaetion** Code *Logic*
- 22 **TDD Code Maker** Agent *Model*
- 23 **Code Reviewer** Agent *Model*
- 24 **Vercel Fixer** Agent *Model*
- 25 **Code1** Code *Logic*
- 26 **Respond to Webhook** Respond To Webhook *Starts it*
- 27 **Generate From MVP Template** Http Request *Service*
- 28 **Parse Output** Code *Logic*
- 29 **Parse Output1** Code *Logic*
- 30 **Parse Code-Fix** Code *Logic*
- 31 **Variables** Code *Logic*
- 32 **Images to generate** Code *Logic*
- 33 **GitHub** Github *Service*
- 34 **Loop-Code** Code *Logic*
- 35 **GitHub Commit Fix** Github *Service*
- 36 **Generate Image** Http Request *Service*
- 37 **Vercel Deploy** Http Request *Service*
- 38 **Merge** Merge *Logic*
- 39 **Wait2** Wait *Logic*
- 40 **If** If *Logic*
- 41 **Wait** Wait *Logic*
- 42 **Vercel Deploy1** Http Request *Service*
- 43 **HTTP Request** Http Request *Service*
- 44 **Vercel Check** Http Request *Service*
- 45 **Wait1** Wait *Logic*
- 46 **If 200** If *Logic*
- 47 **If READY** If *Logic*
- 48 **GH Upload File** Github *Service*
- 49 **return URL** Code *Logic*
- 50 **Vercel Logs** Http Request *Service*
- 51 **Respond to Webhook1** Respond To Webhook *Starts it*
- 52 **Error Logs** Code *Logic*

## How it's built

- **Starts on:** Someone opening a chat with it
- **Steps:** 52, with 3 branches, 3 loops or waits
- **Size:** Large: read it before trusting it with anything live
- **Connects to:** GitHub
- **Model:** OpenAI
- **Retrieval:** Answers are drawn from documents you supply, not from the model alone

## Questions

What does it need to run?

An n8n account, plus your own GitHub account, and a key for OpenAI. You connect your own accounts after importing it; none are included.

What starts it?

It starts on someone opening a chat with it.

Does it use AI?

Yes. It calls OpenAI. Its answers draw on documents you give it, not on the model alone. Model calls are billed by the provider, not by n8n.

How long does it take to set up?

Take your time. At 52 steps it is large: read it before trusting it with anything live.

How do I import it?

Copy the workflow, open a new workflow in n8n and paste. The steps appear on the canvas, ready for your own accounts.

**Before you run it**

Nothing here has been tested by us. It is somebody's working automation, read and described from its own steps. Treat the connections it wants as a list of accounts it will touch, and read the 52 steps before you point it at anything that matters.

## Run it in n8n

- **Create your n8n account** Free to start. n8n is where the workflow runs. [Create an n8n account ↗](https://millionrounds.com/n8n)
- **Download the workflow** Free with a Millionrounds account. [Download free](https://millionrounds.com/login?next=%2Fapp%2Fworkflow%2Fbuild-and-deploy-mvps-from-text-prompts-with-github-and-verc)
- **Paste it into n8n** Open a new workflow in n8n and paste. Then connect your own accounts.

Stored with the author's traces removed: canvas notes, instance identifiers, saved credential names and any live document they had left behind.

## Connects to

Each opens the other workflows that use it.

[GitHub](https://millionrounds.com/workflows?service=GitHub#library)

## Workflows like it

Also ai assistants, with the same services where possible, closest in size first.

- [**Building RAG chatbot for movie recommendations with Qdrant** 25 steps · calls a model · GitHub, Qdrant](https://millionrounds.com/workflow/building-rag-chatbot-for-movie-recommendations-with-qdrant-2)
- [**Building RAG chatbot for movie recommendations with Qdrant** 25 steps · calls a model · GitHub, Qdrant](https://millionrounds.com/workflow/building-rag-chatbot-for-movie-recommendations-with-qdrant)
- [**AI-powered system for Creating & Executing your own Claude Skills** 24 steps · calls a model · GitHub](https://millionrounds.com/workflow/ai-powered-system-for-creating-and-executing-your-own-claude)
- [**Automatic jest test generation for GitHub PRs with OpenAI** 20 steps · calls a model · GitHub](https://millionrounds.com/workflow/automatic-jest-test-generation-for-github-prs-with-openai)
- [**Draft customer-facing changelogs from merged GitHub PRs** 20 steps · calls a model · GitHub, Gmail](https://millionrounds.com/workflow/draft-customer-facing-changelogs-from-merged-github-prs)
- [**Create a code assistant that learns from your GitHub repository** 16 steps · calls a model · GitHub, in-memory vectors](https://millionrounds.com/workflow/create-a-code-assistant-that-learns-from-your-github-reposit)