Exchange Rate MCP Server

Exchange Rate MCP Server

Provides current exchange rates for various currencies via the Model Context Protocol, allowing AI models to fetch real-time currency data.

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README

Exchange Rate MCP Server (Python)

This is a Python implementation of a Model Context Protocol (MCP) server that provides current exchange rates from a reliable source.

Overview

This server implements the Model Context Protocol to provide real-time exchange rate data. It can be used by AI models to get up-to-date currency exchange information.

Features

  • Provides current exchange rates for various currencies
  • Configurable base currency (defaults to USD)
  • Uses the exchangerate.host API as a data source
  • Includes client examples and Ollama integration

Installation

# Clone the repository
git clone git@github.com:devshark/exchange-rate-mcp.git
cd exchange-rate-mcp

# Create a virtual environment
python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

# Install dependencies
pip install -r requirements.txt

# Copy the example environment file and edit as needed
cp .env.example .env

Configuration

Edit the .env file to configure:

  • PORT: The port on which the server will run (default: 3000)
  • EXCHANGE_API_KEY: Your API key for the exchange rate service (optional)

Note about API Keys:

  • The server will work without an API key using free public APIs
  • For testing purposes, you can leave the EXCHANGE_API_KEY empty
  • If the API is unavailable, the server will fall back to mock data

Usage

Starting the Server

python server.py

The server will start on the port specified in your .env file (default: 3000).

Testing with the Client

python client.py

This will send a request to the MCP server and display the response.

Testing with Ollama Integration

First, make sure you have Ollama installed and the gemma3:27b model downloaded:

ollama pull gemma3:27b

Then run the Ollama client:

python ollama_client.py

This will:

  1. Fetch exchange rates from the MCP server
  2. Format them into a prompt
  3. Send the prompt to Ollama
  4. Display and save the response

API

The server exposes an MCP endpoint that accepts JSON-RPC 2.0 requests with the following methods:

listTools

Lists available tools on the server.

Example request:

{
  "jsonrpc": "2.0",
  "id": "1",
  "method": "listTools",
  "params": {}
}

callTool

Calls a specific tool with parameters.

Example request:

{
  "jsonrpc": "2.0",
  "id": "1",
  "method": "callTool",
  "params": {
    "name": "exchange-rates",
    "parameters": {
      "base": "EUR",
      "symbols": ["USD", "GBP", "JPY"]
    }
  }
}

Example response:

{
  "jsonrpc": "2.0",
  "id": "1",
  "result": {
    "content": {
      "base": "EUR",
      "date": "2025-04-12",
      "rates": {
        "USD": 1.0923,
        "GBP": 0.8578,
        "JPY": 163.27
      }
    },
    "metadata": {
      "source": "exchange-rate-mcp",
      "timestamp": "2025-04-12T12:25:30.123Z",
      "baseCurrency": "EUR",
      "symbols": "USD,GBP,JPY"
    }
  }
}

License

MIT

Author

© Anthony Lim

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