Employee Vacation MCP Server

Overview

The Mcp Client Server For Agents is a ready‑to‑deploy Model Context Protocol (MCP) server that simplifies the integration of AI assistants with external data sources. It solves a common pain point for developers: exposing business logic, such as employee vacation balances, in a way that AI agents can discover and invoke without custom adapters. By following the MCP standard, the server presents a clean, versioned API of tools that any compliant client—whether a web UI, a CLI tool, or an AI workflow engine—can consume automatically.

At its core, the server implements two transport mechanisms. The SSE (Server‑Sent Events) variant uses HTTP streaming to deliver real‑time updates, making it ideal for web applications that need continuous feedback from the AI agent. The Stdio variant relies on standard input/output streams, enabling lightweight console or containerized deployments where a persistent HTTP connection is unnecessary. Both variants expose the same logical set of operations: query, update, and manage vacation balances for employees. This consistency ensures that a developer can switch between transport layers without rewriting client code.

Key capabilities of the server include:

• Resource Management – Employees and their vacation balances are stored in an Azure Table emulator, demonstrating how MCP can interface with cloud storage backends.
• Tool Discovery – The server advertises its available tools via the MCP protocol, allowing AI assistants to introspect and generate prompts that invoke specific operations automatically.
• Real‑time Interaction – SSE provides live feedback streams, so an agent can receive incremental results or status updates as it processes a request.
• Cross‑Language Support – Sample implementations are available in both .NET and TypeScript, illustrating the language‑agnostic nature of MCP.

Real‑world scenarios that benefit from this server include HR chatbots that let employees check or request vacation days, automated compliance checks that ensure leave policies are respected, and integration into broader enterprise workflows where AI assistants orchestrate multi‑step processes involving data updates. Because the server follows MCP, developers can plug it into any AI workflow—such as a Copilot Studio or Semantic Kernel pipeline—without writing bespoke connectors. The result is a reusable, maintainable component that bridges the gap between structured business data and conversational AI.