Overview

The Sample MCP Server is a lightweight, TypeScript‑based implementation of the Model Context Protocol (MCP) designed to demonstrate how AI assistants can seamlessly interact with external services. By exposing a well‑structured API surface—comprising resources, tools, prompts, and sampling methods—the server provides a clear blueprint for developers who want to extend an AI’s capabilities without reinventing the wheel.

Solving a Common Integration Gap

When building intelligent applications, developers often face the challenge of connecting an AI model to domain‑specific data or workflows. Traditional approaches require custom adapters, complex authentication flows, and manual state management. The Sample MCP Server eliminates this friction by offering a standardized contract that any MCP‑compliant client can consume. It abstracts away low‑level networking details and presents a consistent interface for querying data, executing business logic, and retrieving formatted responses.

Core Functionality

At its heart, the server implements four key MCP concepts:

• Resources – Structured endpoints that expose data objects (e.g., user profiles, inventory items) and support CRUD operations.
• Tools – Reusable actions that encapsulate business logic, such as calculating shipping costs or validating input against external APIs.
• Prompts – Pre‑defined text templates that can be injected into the AI’s prompt chain, enabling context‑aware interactions.
• Sampling – Controlled response generation strategies that allow the AI to produce deterministic or stochastic outputs based on configured parameters.

These components work together to form a cohesive ecosystem where an AI assistant can request data, invoke logic, and receive contextually rich responses—all through a single protocol.

Real‑World Use Cases

• E‑commerce: An AI assistant can query product availability, calculate discounts, and generate personalized recommendations by leveraging the server’s resources and tools.
• Customer support: The server can expose ticketing data, validate user identities, and retrieve knowledge‑base articles, enabling the assistant to provide accurate and up‑to‑date help.
• Data analysis: By exposing statistical tools and pre‑formatted prompts, the assistant can guide users through complex data queries without requiring them to write code.

Integration into AI Workflows

Developers can plug the Sample MCP Server into existing Claude or other MCP‑enabled assistants with minimal effort. The server’s TypeScript SDK offers type safety and auto‑completion, making it straightforward to define new resources or extend existing ones. Once integrated, the assistant can call tools directly from its prompt logic, automatically passing context and handling responses in a structured manner. This tight coupling reduces latency, improves reliability, and ensures that business rules remain centrally managed.

Distinctive Advantages

• Zero‑Configuration Setup: The server comes pre‑configured with example resources and tools, allowing developers to start experimenting immediately.
• TypeScript First: Strong typing reduces runtime errors and accelerates development cycles, especially valuable in complex domains.
• Modular Architecture: Each MCP concept is isolated, enabling selective deployment or replacement without affecting the entire system.
• Extensibility: New resources, tools, and prompts can be added on top of the existing framework, making the server a living platform rather than a static demo.

In summary, the Sample MCP Server serves as both an educational resource and a practical foundation for building AI‑powered applications that require reliable, protocol‑based interaction with external data and services.