Building a Real-time Chat App (Github MCP + Railway )

In this tutorial, we’ll follow along with Tech With Tim’s Advanced Vibe Coding Tutorial w/ Warp video. You’ll learn how to use Warp, the agentic development environment, to build and deploy a fullstack AI-driven app from scratch — including setup, debugging, and deployment using GitHub MCP servers.

Advanced Vibe Coding Tutorial w/ Warp (Build & Deploy Apps)

Overview

This video shows how to go from idea → working web app → production deployment, all inside Warp. The project: a real-time chat application built with Python (FastAPI) and a JavaScript frontend, deployed through Railway, and integrated with GitHub via MCP (Model Context Protocol).

1

Setup & Installation

Warp is free for Mac, Linux, and Windows. Download it from https://warp.dev and sign in with an account.

Once you open Warp, you’ll see three core modes:

  • Auto Mode – Detects whether you’re typing a command or an AI prompt

  • Terminal Mode – For standard shell commands only (ls, pwd, etc.)

  • Agent Mode – For conversational AI prompts (build me an app, add feature X, etc.)

You can switch modes using the top-bar buttons.

Pro tip: Enable voice input for natural prompting or attach screenshots when debugging UI issues.

2

Generate an App Idea

Warp supports planning models, where the AI generates a detailed roadmap before coding.

The AI suggested several projects, like a personal mood tracker, quick poll creator, recipe randomizer, and more. Chosen idea we went with: a real-time chat application.

3

Create a Development Plan

Prompt:

Warp’s agent generated a plan for:

  • A frontend (UI for chat rooms and messages)

  • A backend (FastAPI server for real-time communication)

  • Database integration and planned deployment steps

You can refine or expand the plan interactively by prompting:

And get back something like this:

At any point, you can go into the plan and start directly modifying it. And when you're ready, you can tell Warp to:

4

Allow Autonomous Execution

Once Warp starts executing, you can let Warp run commands automatically:

  1. Go to Settings → AI → Agents

  2. Change “Always Ask”“Always Allow”

  3. Ensure restricted commands (e.g., rm -rf) remain blocked

This enables autonomous execution for safe, fast iteration. Warp will run shell commands, create directories, initialize files, and write code.

5

Running the App

First, you can click into any file, like main.py to edit it directly in Warp. Warp displays your file directly in the app for easy editing, similar to any regular IDE experience.

You can also ask Warp to run the app and test locally:

It's possible (like in the video) for an error to occur (e.g., Internal Server Error). If that happens, y you can simply debug conversationally:

And Warp can fix the issue and rerun the app automatically.

6

Adding New Features

To enhance the app, request features conversationally:

Warp will modify frontend and backend code, updating WebSocket logic for real-time reactions. After testing, multiple users can now react to messages in the chat interface.

7

Preparing for Deployment

Warp integrates directly with version control and cloud deployers via MCP servers.

Connect GitHub MCP:

  1. Go to Settings → AI → MCP Servers → Add

  2. Add a JSON block for GitHub MCP:

  1. Generate a GitHub personal access token (Settings → Developer Settings → Tokens)

    • Enable scopes for: repo, workflow, secrets, pull_request, and environments.

Save and restart Warp.

Then tell the agent:

Warp uses Git commands automatically:

8

Deploying via Railway

Prompt:

Warp recommends Railway and walks through:

  • Creating a Railway account

  • Connecting your GitHub repo

  • Deploying directly from GitHub

  • Generating a public domain

Once deployed, test it in your browser — you’ll see your live chat app with emoji reactions working in real time.

Appendix

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