You've built an MCP server. It works on your machine. But will it work when your colleague installs it? What about in production?
MCP (Model Context Protocol) servers occupy a unique position in the development stack. They're not traditional REST APIs, and they're not simple CLI tools — they bridge AI models with external resources. This means testing them requires a fundamentally different approach than you might be used to.
After building several MCP servers in production, I've learned that effective testing breaks down into three distinct layers: unit testing for individual functions, integration testing for client/server communication (the layer most developers skip), and end-to-end testing with real AI models.
Let me walk you through each layer with practical examples...
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