Automate Your Testing with Claude, Bun.js, and MCP
Z
Zack Saadioui
8/11/2025
A Game-Changer for Devs: Using Bun.js & MCP to Let Claude Run Your Tests
What’s up, everyone? Hope you’re having a good one. Today, I want to talk about something that's been bubbling up in the dev community & honestly, it feels like we're on the cusp of a major shift in how we build & test software. I’m talking about the combination of ridiculously fast JavaScript tooling, a new open standard for AI interaction, & one of the most powerful AI assistants out there.
We're going to dive deep into using Bun.js, the Model Context Protocol (MCP), & Claude to create a development workflow that feels like it's from the future. Imagine asking your AI assistant to run your test suite & getting the results back instantly, without ever leaving your chat interface. Pretty cool, right? Well, it's not just a hypothetical anymore. Let’s get into it.
First Off, What’s the Big Deal with Bun.js?
If you haven't been living under a rock, you've probably heard the buzz around Bun.js. For the uninitiated, Bun is an all-in-one JavaScript runtime & toolkit. That means it’s a runtime, a package manager, a bundler, & a test runner, all rolled into one blazing-fast package. It was built from the ground up with speed as a top priority, using a low-level language called Zig & the same JavaScriptCore engine that powers Safari.
The result? It’s SIGNIFICANTLY faster than Node.js in many benchmarks. We're talking orders of magnitude faster for things like installing dependencies or running scripts. But the speed is only part of the story. The real magic is in the developer experience.
Here’s a quick rundown of what makes Bun so special:
All-in-One Toolkit: You don't need to juggle npm or yarn, Jest or Mocha, webpack or Rollup. Bun has high-quality, fast tools for all of that built right in. This simplifies your
1
package.json
scripts & your overall project setup immensely. Less configuration, more coding.
Built-in Test Runner: This is a big one for our topic today. Bun comes with a Jest-compatible test runner out of the box. You can write tests with a familiar
1
expect()
API, & it just works—no extra setup required. It’s incredibly fast, which means you’re more likely to run your tests more often.
Native TypeScript & JSX Support: You can just write TypeScript or JSX files & Bun will execute them directly. No more wrestling with
1
ts-node
or complex build configurations. It just works.
Node.js Compatibility: Bun is designed as a drop-in replacement for Node.js. Most Node.js projects & npm packages work with Bun without any code changes, so migrating is often a breeze.
Honestly, starting a new project in 2025 without at least considering Bun feels like a missed opportunity. It streamlines so much of the development process, making it faster & just more fun.
Okay, So What is this "MCP" Thing?
Now for the second key ingredient: MCP, or the Model Context Protocol. This is a bit newer but EQUALLY important. Introduced by Anthropic, the creators of Claude, MCP is an open standard designed to connect AI assistants to external systems.
Think of it like this: by default, large language models (LLMs) like Claude are isolated. They have a ton of knowledge from their training data, but they can't interact with the real world, your private codebase, or your company's internal tools. To bridge this gap, developers have been building custom, one-off integrations for every single tool or data source. It’s a messy, unscalable process.
MCP solves this problem by providing a universal, standardized way for AI models to talk to external tools. It creates a common language for an AI assistant (the "MCP Host") to discover & use tools exposed by an "MCP Server."
This is a HUGE deal. Instead of being a passive Q&A machine, an AI with MCP can become an active agent that can:
Read & write to your local file system.
Interact with databases & APIs.
Run command-line tools.
Browse the web with tools like Puppeteer or Selenium.
Suddenly, the AI can perform actions on your behalf, securely & with your permission. And because it's an open standard, anyone can build an MCP server for their own tools, creating a rich ecosystem of AI-ready applications. We're already seeing this happen, with servers for GitHub, Google Drive, Slack, & more.
The Power Couple: Bun.js Meets MCP
This is where things get REALLY interesting. What happens when you combine the fastest JavaScript toolkit with a universal protocol for AI interaction? You get a workflow that’s both incredibly efficient & powerfully intelligent.
Some brilliant developers have already connected these dots & created the
1
mcp-bun
server. This is a dedicated MCP server built specifically for the Bun runtime. It exposes a whole suite of tools that allow an AI assistant like Claude to interact directly with a Bun-powered project.
According to its GitHub repository, the
1
mcp-bun
server provides tools to:
Run Scripts: Execute any JavaScript or TypeScript file with
1
bun run
.
Manage Packages: Install dependencies with
1
bun install
.
Build Projects: Run
1
bun build
to bundle & minify your code.
And, most importantly, run tests: It has a dedicated
1
run-bun-test
tool that executes tests using Bun's built-in test runner.
This server acts as the perfect bridge. Your Bun project is sitting on your local machine, and the
1
mcp-bun
server provides a secure gateway for Claude to come in & run commands within that project's environment. You can configure it in your VS Code settings or directly in the Claude Desktop app.
Enter Claude: Your New AI Testing Partner
So we have the fast runtime (Bun) & the bridge (MCP). Now we need the brain—and that's Claude.
Claude, especially with the capabilities of recent models, is exceptionally good at understanding code & following instructions. Anthropic has even published best practices for using Claude in a Test-Driven Development (TDD) workflow.
Here's what that workflow looks like:
You ask Claude to write the tests. You describe the feature you're about to build & what the expected inputs & outputs are. You can be explicit that you're doing TDD & that the implementation doesn't exist yet.
Claude writes the test file. It will create a new test file (e.g.,
1
feature.test.ts
) with all the necessary test cases, using the Bun test runner's syntax.
You tell Claude to run the tests. This is the magic moment. Instead of you switching to your terminal & typing
1
bun test
, you just ask Claude: "Okay, run the tests & confirm they fail."
Claude uses MCP to run the tests. Claude, acting as the MCP Host, sends a request to your configured
1
mcp-bun
server. The server then executes the
1
run-bun-test
tool, which runs
1
bun test
in your project directory.
Claude gets the results. The test runner's output (showing all the failures, as expected) is sent back to Claude. Claude can then confirm to you that the tests are failing correctly.
You ask Claude to write the code. Now that you have failing tests, you tell Claude: "Great. Now write the implementation code to make these tests pass. Don't modify the tests."
Claude writes the implementation. It creates or modifies the necessary source files.
Iterate until success. You tell Claude to keep running the tests & fixing the code until everything passes. It will loop through this cycle—running tests via MCP, analyzing the output, & adjusting the code—until the test suite is green.
This is a complete paradigm shift. The AI isn't just writing code in a vacuum; it's an active participant in the entire development loop, using the project's own tools to validate its work in real-time.
So, What Does This Look Like in Practice?
Let's walk through a hypothetical scenario. Say you're building a new e-commerce site & you need to implement a shopping cart function to calculate the total price.
Setup: You have a new project initialized with
1
bun init
. You've installed the
1
mcp-bun
server & configured it in your Claude Desktop app, giving it access to your project's directory.
Prompting Claude: You start a conversation with Claude: "Hey, I need to build a shopping cart calculator for my e-commerce site. Please write the tests for a
1
calculateTotal
function. It should handle multiple items, quantities, & apply a 10% discount if the total is over $100. Write these tests in
1
src/cart.test.ts
."
Claude Writes the Tests: Claude generates the test file, complete with test cases for an empty cart, a single item, multiple items, & the discount logic.
Running the Tests: You say, "Okay, looking good. Run the tests now." Claude uses the
1
mcp-bun
server to execute
1
bun test
. Because Bun is so fast, the feedback is almost instantaneous. Claude replies, "Tests are running... and they've failed as expected. The
1
calculateTotal
function is not defined."
Implementation: You respond, "Perfect. Now create
1
src/cart.ts
& write the
1
calculateTotal
function to make all those tests pass."
Iteration Loop: Claude writes the initial function. You tell it to run the tests again. It comes back: "Okay, 3 out of 4 tests are passing. The discount logic is failing." It shows you the error. You might give it a hint, or just say "Fix it." Claude adjusts the code & reruns the tests. This time, it says, "All tests are passing!"
The entire process happens in a single conversational interface. The feedback loop is incredibly tight, & you're guiding the process at a high level while the AI handles the tedious parts of writing boilerplate & running commands.
Why This is Such a Game-Changer
This workflow is more than just a novelty; it represents a fundamental improvement in developer productivity & experience.
Massively Reduced Context Switching: You stay in one place—your AI chat interface. You're not constantly switching between your editor, your terminal, & your documentation. This keeps you in a state of flow.
Accelerated Feedback Loops: The speed of Bun's test runner combined with the conversational interface means you get feedback on your code's correctness almost instantly. This is the core principle of TDD, supercharged.
Focus on What Matters: You get to focus on the "what" (the logic, the requirements, the architecture) while the AI handles the "how" (the syntax, the boilerplate, the command execution). This frees up your brainpower for more creative problem-solving.
Democratizing Powerful Workflows: Setting up complex testing & automation pipelines can be a huge pain. This approach simplifies it dramatically. Any developer can now leverage a sophisticated, AI-driven TDD workflow without being a CI/CD expert.
This kind of automation is becoming more accessible for all sorts of business processes. For example, a lot of companies are now looking at how to automate their customer support. This is where a platform like Arsturn comes in. Arsturn helps businesses create custom AI chatbots trained on their own data. These chatbots can provide instant customer support, answer questions 24/7, & engage with website visitors, freeing up human agents to focus on more complex issues—much like how this dev workflow frees up developers. The underlying principle is the same: leveraging AI to handle repetitive tasks so humans can focus on high-value work.
For businesses looking to automate lead generation or customer engagement, this kind of tech is invaluable. With Arsturn, you can build no-code AI chatbots that are trained on your business's specific documents & website content. This allows them to provide personalized customer experiences, boost conversions, & build meaningful connections with your audience, all automatically.
Hope This Was Helpful!
Look, we're just scratching the surface of what's possible here. The tools are still evolving, but the path forward is becoming clear. The fusion of fast, integrated development tools like Bun.js & intelligent, tool-using AI agents like Claude is set to redefine our workflows.
It might feel a little strange at first to "talk" your code into existence, but I encourage you to give it a try. Set up a small project with Bun, get the
1
mcp-bun
server running, & start a TDD session with Claude. I think you'll be amazed at how fluid & powerful it feels.
Let me know what you think. Have you tried this workflow? Are there other cool tool combinations you're excited about? Drop a comment below! Catch you in the next one.