Christopher Harrison explains how to leverage GitHub Copilot and the Playwright MCP server to reproduce and debug web app issues, sharing practical setup steps and real debugging workflows.

How to Debug a Web App Using Playwright MCP and GitHub Copilot

Christopher Harrison explains how using GitHub Copilot in agent mode, together with the Playwright MCP (Model Context Protocol) server, can greatly simplify the process of reproducing, diagnosing, and resolving web application bugs.

Automating Bug Reproduction

Debugging web apps usually starts with reproducing the reported issue. Even when users provide clear steps, going through those steps can be tedious. Playwright, an end-to-end testing framework, can help by automating UI testing. However, manually writing test scripts can still be time-consuming.

By integrating the Playwright MCP server with GitHub Copilot, you allow Copilot’s agent mode to run those steps automatically in VS Code. The MCP protocol acts as a bridge, enabling AI agents (like Copilot) to control Playwright and execute user-provided reproduction steps, validate issues, and even help fix them.

What Are Playwright and MCP?

Playwright: A widely-used, open-source end-to-end testing framework for web apps. It can automate user interaction flows, verify features, and help ensure app quality.
MCP (Model Context Protocol): An open protocol for exposing tools to AI agents. Through the Playwright MCP server, Playwright scripts and capabilities become accessible to Copilot.

Setting Up Playwright MCP with Copilot in VS Code

Install the Playwright MCP server in VS Code:
- Use the official installation command or configure by adding a mcp.json file inside your .vscode folder with the following:
```
{
  "servers": {
    "playwright": {
      "command": "npx",
      "args": ["@playwright/mcp@latest"]
    }
  }
}
```
Start the server:
- Press the play button in VS Code (it appears above “playwright” in the mcp.json) to start the MCP server for your project.
Configure Playwright:
- Make sure your app’s startup procedure is handled in Playwright’s config (see documentation). This can be automated in part with Copilot agent mode prompts.

Real-World Debugging Example

Suppose you’re working on a crowdfunding platform for DevOps-themed board games, and a user reports that the “publisher filter” isn’t working. The issue provides full reproduction steps. Instead of manually testing, you prompt Copilot’s agent mode to:

Use Playwright MCP to walk through the repro steps
Confirm whether the bug exists
Inspect the relevant frontend and backend code

Copilot, aided by Playwright MCP, follows those steps in an isolated test, confirms the bug, and even suggests a fix (such as correcting a typo in the backend code). It then re-tests after applying the fix, verifying that the issue is resolved.

Benefits of Playwright MCP + Copilot for Debugging

Faster diagnosis: Automate repetitive validation steps and focus on complex analysis
AI-powered exploration: Let Copilot try out solutions, create configuration files, and generate tests
Deeper integration: Use Copilot to automate not just code completion, but actual application testing and bug triage
Easier onboarding: New contributors can leverage agent mode to quickly understand and test web app behaviors

Additional Resources

By integrating Playwright MCP and GitHub Copilot, debugging and fixing web application issues becomes a more automated, reproducible, and developer-friendly process.

This post appeared first on “The GitHub Blog”. Read the entire article here