Exchange Rate Mcp

Overview

The Exchange Rate MCP Server bridges the gap between AI assistants and real‑time foreign‑exchange data by exposing a single, well‑defined tool: . Built on top of the Norges Bank API, this server delivers currency conversion rates with minimal latency and a straightforward interface that fits naturally into the Model Context Protocol ecosystem. Developers can invoke the tool from any MCP‑compatible client—Claude, GPT‑4o, or custom agents—to retrieve the most recent or historical exchange rates without leaving their workflow.

Solving a common data‑access problem

AI assistants frequently need up‑to‑date financial information to answer user queries, generate reports, or power automated trading signals. Traditionally, developers would have to embed API keys, manage HTTP requests, and parse JSON responses manually. The Exchange Rate MCP abstracts these concerns behind a declarative tool call. By simply supplying , , and an optional , the assistant can obtain a clean, typed response that includes both metadata and the numeric rate. This eliminates boilerplate code and reduces the risk of errors such as incorrect currency codes or malformed dates.

Key features

• Single‑point tool: The method is the only exposed capability, making it easy to discover and use.
• Optional historical lookup: Passing a parameter retrieves rates for that day; omitting it defaults to the most recent available rate, supporting both real‑time and archival use cases.
• Transparent data structure: The response echoes the request parameters along with the computed rate, enabling downstream components to validate and log exchanges effortlessly.
• Norges Bank data source: Leveraging a reputable, publicly available API ensures reliability and compliance with Norwegian financial regulations.

Real‑world use cases

• Travel budgeting: An AI assistant can quickly convert a user’s travel expenses into their home currency, helping them plan itineraries.
• Financial reporting: Automated systems can refresh balance sheets with current exchange rates before generating quarterly reports.
• Currency‑aware recommendation engines: E‑commerce platforms can adjust pricing or shipping estimates based on real‑time rates.
• Educational tools: Language learning apps can illustrate how currency values fluctuate over time, using historical dates.

Seamless integration into AI workflows

Because the tool adheres to MCP conventions, it can be invoked directly from a prompt that includes an statement. The assistant sends the request, receives the structured JSON response, and can embed it in a subsequent natural‑language answer or pass it to another tool (e.g., a calculator) without additional parsing. This declarative style keeps the conversation flow natural while ensuring that the underlying data remains accurate and auditable.

Standout advantages

• Zero‑configuration: The server runs with a single command and requires no API keys, making it ideal for quick prototypes or educational demos.
• Lightweight footprint: As a toy project, it demonstrates how MCP servers can be built quickly in JavaScript/TypeScript, encouraging experimentation.
• Open‑source transparency: Developers can inspect the codebase to understand how currency codes are validated and how dates are parsed, fostering trust in the tool’s outputs.

In summary, the Exchange Rate MCP Server offers a focused, dependable solution for embedding foreign‑exchange data into AI‑driven applications. Its simplicity, coupled with the robust capabilities of the Norges Bank API, makes it a valuable asset for developers seeking to enrich their assistants with real‑world financial intelligence.