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Java MCP Server

MCP Server

Demo server built with the official MCP-JAVA-SDK

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Updated Mar 30, 2025

About

A lightweight demonstration of the MCP-Java SDK, showcasing how to implement a basic MCP server for Java applications. It serves as a starting point for developers looking to integrate MCP services into their Java projects.

Capabilities

Resources
Access data sources
Tools
Execute functions
Prompts
Pre-built templates
Sampling
AI model interactions

Overview

The Java Map Component Platform (Java MCP) is a Spring Boot‑based server that exposes a rich set of geospatial services through the Model Context Protocol. It solves the common problem of integrating map‑related functionality—such as geocoding, weather lookup, POI discovery, routing, and distance calculation—into AI‑driven applications. By packaging these capabilities behind a standard MCP endpoint, developers can let AI assistants query real‑world location data without writing custom adapters or handling API keys directly.

At its core, the server offers a single MCP integration path () that bundles all map services. Each operation (e.g., , , ) accepts simple query parameters and returns structured JSON, making it trivial for an AI model to consume the results. The platform also provides separate RESTful namespaces (, , etc.) for traditional web usage, giving teams flexibility to use the same code base in multiple contexts.

Key features include:

  • Geocoding & Reverse Geocoding – Convert addresses to coordinates and vice versa, supporting optional city hints for disambiguation.
  • Weather Lookup – Retrieve current weather by city name or administrative code, enabling AI assistants to answer climate‑related queries.
  • POI Search & Details – Keyword, nearby, and type‑filtered searches return comprehensive point‑of‑interest data, while fetches full information for a specific POI.
  • Routing – Multi‑modal path planning (walking, biking, driving, transit) with origin/destination coordinates and city context.
  • IP Location & Distance Measurement – Resolve IP addresses to locations and compute straight‑line, driving, or walking distances between points.

Real‑world scenarios are abundant: a travel chatbot can suggest nearby attractions, a logistics assistant can calculate optimal delivery routes, or a weather bot can provide localized forecasts. In AI workflows, the MCP server acts as a trusted data source; the assistant sends a request via the endpoint, receives structured results, and incorporates them into natural language responses or further processing steps.

What sets this server apart is its tight integration with the MCP ecosystem and its lightweight Spring Boot implementation. It requires only a single API key for the underlying map provider, automatically handles request routing, and exposes both a unified MCP interface and granular REST endpoints. This dual exposure simplifies adoption for developers familiar with either protocol, while the comprehensive documentation and modular architecture make extending or customizing features straightforward.