This project demonstrates how to integrate Spring AI's MCP (Model Context Protocol) within Spring Boot applications, covering server-side and client-side implementations for geographical data processing, including city geocoding and timezone information retrieval.
Added on:
Created by:
Mar 18 2025
This project demonstrates how to integrate Spring AI's MCP (Model Context Protocol) within Spring Boot applications, covering server-side and client-side implementations for geographical data processing, including city geocoding and timezone information retrieval.
Added on:
Created by:
Mar 18 2025
Omar Alles
Featured
What is Spring AI MCP Test?
The Spring AI MCP Test project provides a comprehensive setup for managing geographical data through MCP in Spring Boot. It includes services for geocoding cities to obtain latitude and longitude, and retrieving timezone information based on coordinates. The MCP Host acts as an interface, allowing users to interact via console, using tools to gather accurate geographic and timezone data. It leverages Spring AI to facilitate the communication with MCP servers and clients, making it suitable for developers needing geographic data integration in AI workflows.
Who will use Spring AI MCP Test?
- Developers working on AI and geospatial applications
- Spring Boot developers integrating MCP
- AI solutions involving geographical data
- Researchers in geospatial data processing
How to use the Spring AI MCP Test?
- Step1: Start the Geocoder Service with 'mvn spring-boot:run' in the geocoder module.
- Step2: Start the Timezone Service similarly in the timezone module.
- Step3: Start the MCP Host application to enable interaction.
- Step4: Enter city names in the console to get latitude, longitude, and timezone info.
Spring AI MCP Test's Core Features & Benefits
The Core Features
- Geocode city to latitude and longitude
- Retrieve timezone info from coordinates
- Interact via console for geographical data queries
The Benefits
- Simplifies geographic data integration in Spring Boot
- Facilitates MCP communication between services
- Provides real-time geographic and timezone data
Spring AI MCP Test's Main Use Cases & Applications
- Geographical data integration in AI applications
- Location-based timezone services
- Geospatial research and development
- Geocoding for travel or logistics platforms
FAQs of Spring AI MCP Test
Developer
- oalles
You may also like:
Developer Tools
A desktop application for managing server and client interactions with comprehensive functionalities.
A Model Context Protocol server for Eagle that manages data exchange between Eagle app and data sources.
A chat-based client that integrates and uses various MCP tools directly within a chat environment for enhanced productivity.
A Docker image hosting multiple MCP servers accessible through a unified entry point with supergateway integration.
Provides access to YNAB account balances, transactions, and transaction creation through MCP protocol.
A fast, scalable MCP server for managing real-time multi-client Zerodha trading operations.
A remote SSH client facilitating secure, proxy-based access to MCP servers for remote tool utilization.
A Spring-based MCP server integrating AI capabilities for managing and processing Minecraft mod communication protocols.
A minimalistic MCP client with essential chat features, supporting multiple models and contextual interactions.
A secure MCP server enabling AI agents to interact with Authenticator App for 2FA codes and passwords.
Research And Data
A server implementation supporting Model Context Protocol, integrating CRIC's industrial AI capabilities.
Provides real-time traffic, air quality, weather, and bike-sharing data for Valencia city in a unified platform.
A React application demonstrating integration with Supabase via MCP tools and Tambo for UI component registration.
A MCP client integrating Brave Search API for web searches, utilizing MCP protocol for efficient communication.
A protocol server enabling seamless communication between Umbraco CMS and external applications.
NOL integrates LangChain and Open Router to create a multi-client MCP server using Next.js
Connects LLMs to Firebolt Data Warehouse for autonomous querying, data access, and insight generation.
A client framework for connecting AI agents to MCP servers, enabling tool discovery and integration.
Spring Link facilitates linking and managing multiple Spring Boot applications efficiently within a unified environment.
An open-source client to interact with multiple MCP servers, enabling seamless tool access for Claude.
AI Chatbot
Integrates APIs, AI, and automation to enhance server and client functionalities dynamically.
Provides long-term memory for LLMs by storing and retrieving contextual information via MCP standards.
An advanced clinical evidence analysis server supporting precision medicine and oncology research with flexible search options.
A platform collecting A2A agents, tools, servers, and clients for effective agent communication and collaboration.
A Spring-based chatbot for Cloud Foundry that integrates with AI services, MCP, and memGPT for advanced capabilities.
An AI agent controlling macOS using OS-level tools, compatible with MCP, facilitating system management via AI.
PHP client library enabling interaction with MCP servers via SSE, StdIO, or external processes.
A platform for managing and deploying autonomous agents, tools, servers, and clients for automation tasks.
Enables interaction with powerful Text to Speech and video generation APIs for multimedia content creation.
An MCP server providing API access to RedNote (XiaoHongShu, xhs) for seamless integration.