MCP Claude Desktop Demo Server

Overview

The MCP Server with Claude Desktop – Interactive Tool API Demo showcases how a lightweight MCP (Modular Claude Protocol) server can expose a set of practical tools and resources that AI assistants such as Claude can consume in real time. By running the server with the FastMCP framework, developers gain a plug‑in style interface that turns everyday tasks—calculations, note management, and currency conversion—into first‑class API endpoints. This eliminates the need for bespoke integrations or manual data handling when building AI‑powered applications.

At its core, the server offers three arithmetic tools (add, subtract, multiply, divide) that perform error‑checked numeric operations. A currency exchange tool pulls live rates from a public API, enabling agents to provide up‑to‑date financial information without embedding external services directly in the assistant. The sticky notes tool reads from and writes to a local file, allowing the assistant to persist user thoughts and later generate concise summaries. These capabilities are surfaced as MCP resources, making them discoverable and callable by any compliant client.

Key features include:

• Dynamic Greeting Resource – lets the assistant generate personalized greetings on demand.
• Latest Note Retrieval – fetches the most recent entry, streamlining follow‑up interactions.
• Prompt Templates – Predefined prompts such as or enable the assistant to format responses or construct further queries automatically.
• Error Handling – Arithmetic tools validate inputs, ensuring that the assistant receives reliable results even when users provide malformed data.

The server is ideal for developers building conversational agents that require quick, reliable access to small but essential utilities. For instance, a budgeting chatbot can ask the exchange tool for real‑time rates before suggesting currency conversions. A study helper can add and retrieve notes, then ask the assistant to summarize key points before a test. By exposing these tools through MCP, developers can keep their AI workflows modular and maintainable, swapping out or extending functionalities without touching the core assistant code.

What sets this demo apart is its simplicity and extensibility. The FastMCP framework handles the heavy lifting of HTTP routing, serialization, and resource registration, while developers focus on defining tool logic. The server’s design encourages rapid prototyping: adding a new calculator function or a weather lookup tool involves writing a small Python routine and registering it as an MCP resource. Once registered, any Claude client—desktop, CLI, or web—can invoke the tool with natural language or programmatic calls, making it a powerful foundation for building intelligent, data‑aware applications.