Overview

The MCP Server Template is a ready‑to‑use starter kit that demonstrates how to build an AI tool server with the Model Context Protocol (MCP) using the lightweight Bun runtime. Its primary purpose is to provide developers with a concrete example of an MCP‑compatible service that can be integrated into AI assistants such as Claude. By focusing on a quiz domain, the template shows how to expose structured data and interactive capabilities through MCP tools while keeping the implementation simple enough for rapid experimentation or extension.

What Problem Does It Solve?

Developers building AI assistants often need external services that can answer domain‑specific queries or provide dynamic content. Writing such a service from scratch requires setting up an HTTP server, defining JSON schemas, handling authentication, and ensuring compatibility with the MCP specification. The template eliminates this boilerplate by offering a pre‑configured server that already implements the MCP protocol, exposes a single “get_quiz” tool, and includes end‑to‑end testing. This allows teams to jump straight into adding their own business logic—such as new quiz categories, scoring algorithms, or integrations with databases—without worrying about the underlying protocol plumbing.

Server Functionality and Value

At its core, the server implements a single interactive tool called . When invoked, it returns a set of quiz questions tailored to the requested category (e.g., science, history) and difficulty level (easy, medium, hard). The response is fully typed using a JSON schema, ensuring that AI assistants can validate the data before consumption. Because MCP emphasizes low‑latency, stateless communication, this tool can be called repeatedly in a conversational loop, enabling assistants to quiz users on the fly or embed trivia into broader workflows.

For developers, this is valuable because it demonstrates how to:

• Expose domain logic through a clean MCP tool interface.
• Validate inputs and outputs with declarative schemas, reducing runtime errors.
• Integrate testing via Jest to guarantee that the MCP contract remains intact as the code evolves.
• Leverage Bun’s fast startup and efficient module resolution to keep the server lightweight.

Key Features Explained

• Category & Difficulty Selection – The tool accepts two optional parameters, allowing fine‑grained control over the question set. This flexibility is useful for tailoring quizzes to different audiences or difficulty requirements.
• Extensible Question Store – The object is a simple in‑memory data structure that can be replaced with a database or external API without changing the MCP interface. Adding new categories is as easy as extending this object and updating the schema.
• Comprehensive Test Coverage – The repository includes integration tests that exercise the MCP endpoint, ensuring that schema changes do not break compatibility.
• Bun Runtime – By using Bun, the server benefits from rapid startup times and a modern JavaScript/TypeScript ecosystem without the overhead of Node.js.

Real‑World Use Cases

• Educational Platforms – Embed a quiz tool into an AI tutor that can generate questions on demand, track progress, and adapt difficulty based on user performance.
• Gamified Customer Engagement – Use the tool to create trivia challenges within a chatbot, encouraging users to interact with brand content.
• Interactive Training Modules – Incorporate the quiz tool into corporate training assistants, allowing employees to test knowledge in real time.
• Research Prototyping – Quickly prototype data‑driven AI applications that require dynamic question generation, such as linguistic studies or cognitive assessments.

Integration with AI Workflows

To connect the server to an AI assistant, a simple configuration entry specifies the command that launches the Bun process and points to the server’s entry point. Once running, the assistant can invoke via the MCP tool call syntax shown in the README. The response is immediately usable by the assistant’s language model, which can format it into a friendly prompt or embed it within a larger conversational context. Because the server is stateless, scaling can be achieved by running multiple instances behind a load balancer or deploying to serverless platforms.

Unique Advantages

• Zero Boilerplate MCP – The template removes the friction of setting up an MCP server, letting developers focus on domain logic.
• Bun‑Optimized – Faster startup and lower memory footprint compared to traditional Node.js setups, ideal for high‑frequency quiz requests.
• Test‑First Design – Built‑in Jest tests encourage a robust development workflow and provide confidence when extending the toolset.
• Clear Documentation – The README serves as both a usage guide and a technical reference, making onboarding straightforward for new contributors.

In summary, the MCP Server Template offers a concise, well‑structured foundation for