Table of Contents
How AI-Powered Agents Are Transforming Browser Functional Testing with Selenium and Playwright 1
1. Introduction: The New Era of Testing.
2. Why Functional Testing Needs AI
Automated Functional Testing with MCP.
3. Meet the Servers: Selenium vs. Playwright in MCP.
4. Demonstration: From Prompt to Report
1. Introduction: The New Era of Testing
Functional testing has always been a cornerstone of software quality. Functional testing has been for a long time both manual and automated. But in the age of AI and automation, the way we test is evolving. Many software testing tools have hit the market designed to fulfill the automated testing needs each having its own language. Test Analysts have had to know manual testing to meet the needs of low budget projects. Many of these analysts have been exposed to various automation tools that help them meet expensive project testing requirements.
Enter the Model Context Protocol (MCP)—a framework that allows intelligent agents to interact with tools like Selenium and Playwright in real time. This new protocol is taking automation testing to a new level. It is opening the test automation world to all test analyst. They do not need to know the language of the preferred test tool. They simply need to know how to draft good AI prompt statements or questions.
In this article, we explore how MCP servers are revolutionizing browser-based testing, enabling AI agents to not only execute tests but also interpret results, adapt scripts, and even generate new test cases.
2. Why Functional Testing Needs AI
Traditional testing frameworks are powerful—but they’re also static. They require:
- Manual script writing
- Rigid test flows
- Human interpretation of results
With MCP, testing becomes dynamic and more intelligent. Agents like Claude can:
- Generate test scripts from natural language
- Execute tests across browsers
- Analyze failures and suggest fixes
- Adapt tests based on UI changes
Let’s compare three key methods of functional testing—Manual, Automated, and Automated with MCP (Model Context Protocol)—along with their evolutionary path:
Manual Functional Testing
The core of manual testing is to define and execute test cases step-by-step to ensure the software targeted meets business, technical, and test requirements. This approach is sometimes costly due to the amount of time required. Yet sometimes there is a less expensive route when only one person is needed to meet the test requirements.
But there are pros and cons to manual testing. Manual testing is good exploration and ad-hoc testing. It’s good when you need to be flexible and intuitive. It is especially great for early-stage or rapidly changing features.
But it has limitations related to time, errors, scalability, and use cases. Manual testing can be time-consuming, error-prone, and not scalable. It is usually limited to small projects. Big projects can require too many people to get the job done. When test requirements include multiple regression test cycles, cost control can become challenged.
Automated Functional Testing
The essence of automated functional testing is developing test scripts that are written and executed using tools (e.g., Selenium, Playwright, UFT, and Cypress). A challenge that comes with that is the number of free and costly products. Which one will truly meet the need and how many analysts know the tool.
The tools I mentioned as an example and there are many others, are all fast, repeatable, and scalable. They are excellent for regression, load, and cross-platform testing. But they have limitations too.
Thought you can elect to use an open-source tool because it’s free, that does not eliminate other costs. There can be high setup and maintenance cost. There can be challenges around dynamic or highly visual interfaces where the tool is just not flexible enough. When it comes to testing highly-secured software applications, some test tools are also not flexible enough to address the dynamics of the software. For instance, SAP, Salesforce, and Oracle business applications are not supported by all test tools. My point is that tools don’t come without limitations.
Automated Functional Testing with MCP
The spirit of combining automation test tools with MCP is more adapted to AI-driven systems where behavior is context-sensitive and probabilistic. In other words, test automation is not prone to complete only if there is no failure. This approach to testing is revolutionary. It is destined to replace traditional approaches to testing.
Automation testing is strengthened with the use of method context protocol because it causes a go-between in the midst of the test analyst and the automation test tool. I may decide that automation test tool (ABC) is my tool of choice for testing the target application, but I am not concerned about the language of the test tool. My language is the same for any tool I select. And my MCP client is designed to take my AI prompts and proceed with dialoging with the test tool until it gets results for me to see and review.
The approach is strong in that it handles dynamic, non-deterministic outputs. And it uses AI to simulate user contexts, validate model behavior, and detect drift or bias. It makes browser testing even more visible because I can still see the browser navigation in real time, and I can see the requests and responses the AI agent or MCP client is showing. So, I don’t have to wait until the test is completed. I see results in real time.
Now, granted there are still some limitations. The MCP client and MCP Server must be advanced enough to manage requests and verification or validation responses. And that includes good error handling to avoid unnecessary test failures. Another limitation is that traditional pass/fail logic often is replaced with statistical or contextual validation.
In a short time, this approach is becoming more received. There are many thousands of MCP services available to dialog with business applications and other software tools. And the benefits are increasing steadily.
What is the Evolution Path
Whatever the new approach will finally be called is not yet certain, but we will see movement from the tradition. Many have experienced movement from test projects that only require manual testing. Some have seen automation only test projects. A transitionary period will begin soon for test projects to include MCP technology. And it is possible to see test projects only require Context-driven testing.
Human-centric Testing → Script-driven Testing → Context-driven Testing
| Human-centric | Script-driven | Context-driven |
| Exploratory | Scalable | Adaptive |
| Intuitive | Repeatable | Intelligent |
We have been trying to make the first-level migration or transition mentioned in item 1 below. And now it is certain that the second-level migration will take shape as itemized in item 2 below.
- Manual → Automated: Driven by the need for speed, scale, and CI/CD integration.
- Automated → MCP & Manual → MCP: Driven by the rise of AI/ML systems where behavior is no longer deterministic.
3. Meet the Servers: Selenium vs. Playwright in MCP
I mentioned that there are many test tools on the market today. We may lose some with this new approach to testing. And there is a growing number of MCP Servers that are being created usually by the owner of the test tool to keep their product relevant. But I cannot talk about all of these products. I have selected the two I use the most.
One thing to be careful with is some tools have a duplication of efforts. There may be more than one MCP server available for a particular product. Choose the one that was done by the vendor of the product if it is available.
So, my two test tools of choice are Selenium and Playwright. I am not saying by selecting these two that they are the best. They are open-source and free. That means they are within my budget, and they are readily available. However, in my demonstration video to accompany this article you will see some unexpected surprises.
MCP is causing interest from people who want to be ahead of the herd. What I mean by that is when some of us see a good thing, we want to get ahead of others. To be more specific, we don’t just have one registry site for MCP clients, servers, and MCP documentation. We may not even have one community site for MCP. The number grows often by day. And we don’t just settle for one MCP server per product. For instance, my choosing Playwright and Selenium test tools to test out the MCP concept means I have to choose which MCP for Selenium and which MCP for Playwright server I should use for my demonstrations. In fairness, I am not the only one writing about MCP. I am not the first and I won’t be the last. Many of us are just trying to be helpful. You have to figure out who we are. 😊
So, in your choosing it is prudent to think about strengths, limitations, and what the test tools are best-known for. Many times, security and ease of use play a big role as well. But with the idea of MCP you might not care how challenging the tool’s language is because you are abstracted from it.
Here are my descriptions of the two tools I have chosen to compare:
Choice #1: Selenium MCP Server
- Strengths: Cross-browser support, legacy compatibility
- Limitations: Slower execution, less modern syntax
- Best For: Regression testing, enterprise apps
Choice #2: Playwright MCP Server
- Strengths: Fast, modern, supports multiple contexts
- Limitations: Newer ecosystem
- Best For: Modern web apps, parallel testing
Both servers should expose a standardized MCP interface, allowing agents to interact with them using structured prompts and contextual memory. My MCP client choice is Claude Desktop which can interface with both MCP servers chosen.
4. Demonstration: From Prompt to Report
In the accompanying video I will walk through a real-world scenario using a sample application known as Swag Labs:
🧑💻 Prompts:
- “Test the login flow on the saucedemo.com site with user called locked_out_user and verify that incorrect credentials show an error message.”
- “Verify login on the saucedemo.com site with user called standard_user. Verify user login and selection of the first product image to display product item page, and then logout.”
| 🤖 Agent Action for prompt 1: | 🤖 Agent Action for prompt 2: |
| Generates a test script (Selenium or Playwright) | 1. Generates a test script |
| Launches the browser | 2. Launches the browser |
| Navigates to the login page | 3. Navigates to the login page |
| Inputs invalid credentials | 4. Inputs valid credentials |
| Verifies the error message | 5. Navigates to the product page |
| Captures a screenshot | 6. Captures a screenshot |
| Logs the result | 7. Selects product 1 image with a click |
| 8. Navigates to the product item page | |
| 9. Logs out and logs results | |
| 📊 Result: | 📊 Result: |
| Pass/Fail status | Pass/Fail status |
| Screenshot of the result | Screenshot of the result |
| Suggested improvements (e.g., add test for password reset) | Summary Data (e.g., information that confirms actions) |
5. Why Does This Matter
This isn’t just automation—it’s intelligent collaboration. Test Analysts can now:
- Focus on verification and validation, not coding efforts
- The possibility of catching regression issues earlier with good understanding of the issue
- Maintain test coverage with less effort having the prompt as the test asset. No code must be kept and maintained unless an alternate backup is required. This exception would be a way to handle when MCP clients are failing reusability.
- And QA teams can scale their efforts without scaling headcount.
6. Looking Ahead
As MCP servers mature, we’ll see multi-agent test orchestration, visual regression testing, and self-healing test suites. Let me dig further:
- Multi-agent test orchestration – a testing strategy where multiple AI agents like Claude are used to collaborate on testing tasks. This involves defining different roles for each agent, specifying which agents are responsible for which tasks, and managing the interactions between them. This might be useful for parallel or multi-browser testing.
- Visual regression testing – also known as visual validation testing or just visual testing. The idea is to be able to verify by comparison any screen visual changes.
- Self-healing test suites – a testing methodology where automated tests can automatically adapt and repair when changes occur with target test applications. Instead of requiring manual intervention, self-healing test suites use AI and ML to detect and fix issues, ensuring that tests remain valid and reliable even as the application matures.
The future of testing is not just automation. Now, it’s becoming adaptive, contextual, and AI-driven.
7. Conclusion
Functional testing is no longer a bottleneck in the application development project. With MCP servers and AI agents, it becomes a strategic advantage. Whether you’re using Selenium for legacy systems or Playwright for modern apps, the combination of MCP and intelligent agents brings confidence to every code change.
If you have never used an automation tool before for testing or you are wanting to do more automation testing, testing with AI and MCP is an easy way to bring big benefits to your project. It will catapult you forward in the world of functional testing.
It is also worth noting that Application developers may find this approach to testing as helpful as debugging tools have become. Maybe Test-driven development may see benefits as well. Some things to consider.
8. Follow-On
Not only do I have a video to accompany this article. But I have an extension article. It is entitled “More on AI-Powered Agents Transforming Browser Functional Testing with Selenium and Playwright”. It is intended to pick up roughly where this article ends. When you see the video, there will be changes from the original plan I had. So, this article will serve to fill you in on some missing details. I think it is an enhancement to this article as well as the video. You can watch the video and read the other article in either order. I recommend reading the articles first, and the watch the video.