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Kotlin Crypto Price Spring MCP Server Demo

Kotlin Crypto Price Spring MCP Server Demo

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github.com/gaplo917Finance3Updated 81w ago
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About Kotlin Crypto Price Spring MCP Server Demo

This Kotlin and Spring Boot demo exposes CoinGecko cryptocurrency search and market data through a Spring AI MCP server. It is intended for AI models and MCP clients that need cryptocurrency information.

Key features

  1. 01Search coins, exchanges, categories, and NFTs
  2. 02Retrieve cryptocurrency market data
  3. 03Expose capabilities through Spring AI MCP
  4. 04Log tool requests and responses

Use cases

  1. 01Search for cryptocurrency information by name or symbol
  2. 02Retrieve market data using a cryptocurrency ID

MCP support

The Spring AI MCP server exposes cryptocurrency search and market-data retrieval as tools for MCP clients and compatible AI models.

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

No install method listed yet

We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.

Repository

Tools

No tool list yet

Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.

Details

From the project README

Kotlin Crypto Price Spring MCP Server Demo

A demonstration project showcasing the integration of Spring AI's Model Context Protocol (MCP) server with a cryptocurrency price API service. This project allows AI models to retrieve real-time cryptocurrency information through a standardized interface.

Overview

This project implements a Spring Boot application that serves as an MCP server, providing tools for AI models to:

  1. Search for cryptocurrencies by name or symbol
  2. Retrieve market data for specific cryptocurrencies

The application uses the CoinGecko API to fetch real-time cryptocurrency data.

Features

  • Cryptocurrency Search: Search for cryptocurrencies, exchanges, categories, and NFTs
  • Market Data Retrieval: Get detailed market data for specific cryptocurrencies
  • MCP Integration: Exposes functionality as tools for AI models via Spring AI's MCP server
  • Logging: Comprehensive logging of tool requests and responses

Technologies

  • Kotlin 1.9.25
  • Spring Boot 3.4.4
  • Spring AI MCP Server
  • Model Context Protocol SDK 0.8.1
  • Java 21

Project Structure

src/main/kotlin/org/gaplo917/mcpservercoinprice/
├── CoinPriceService.kt         # Service for cryptocurrency data retrieval
├── McpServerCoinPriceApplication.kt  # Main application class

Getting Started

Prerequisites
  • JDK 21 or higher
  • Gradle
Running the Application
./gradlew bootRun

The MCP server will start on the default port (typically 8080).

API Tools

The application exposes the following tools for AI models:

1. Search Cryptocurrency
@Tool(description = "search cryptocurrency information by user input query.")
fun searchCryptocurrency(query: String): CryptoData
2. Get Market Data
@Tool(description = "get cryptocurrency market data by id. The id must be used by the return of the searchCryptocurrency tools.")
fun getMarketDataByCryptocurrencyId(id: String): CryptoMarketData

Data Models

  • CryptoData: Contains lists of coins, exchanges, categories, and NFTs
  • CryptoMarketData: Contains market data including tickers for a specific cryptocurrency
  • Coin: Represents a cryptocurrency with its ID, name, symbol, and market cap rank
  • Ticker: Contains trading information for a cryptocurrency on a specific market

Integration with AI Models

This server can be used with AI models that support the Model Context Protocol (MCP), allowing them to retrieve cryptocurrency data in a standardized way. The Spring AI MCP Server handles the communication between the AI model and the cryptocurrency service.

License

This project is licensed under the terms included in the LICENSE file.

References

Comments

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New to MCP?

From what the protocol is to installing your first server, these answers cover most first questions.

An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.