Spring AI MCP Weather Server Sample with WebFlux Starter

This sample project demonstrates how to create an MCP server using the Spring AI MCP Server Boot Starter with WebFlux transport. It implements a weather service that exposes tools for retrieving weather information using the National Weather Service API.

For more information, see the MCP Server Boot Starter reference documentation.

Overview

The sample showcases:

• Integration with spring-ai-mcp-server-webflux-spring-boot-starter
• Support for both SSE (Server-Sent Events) and STDIO transports
• Automatic tool registration using Spring AI's @Tool annotation
• Two weather-related tools:
  • Get weather forecast by location (latitude/longitude)
  • Get weather alerts by US state

Dependencies

The project requires the Spring AI MCP Server WebFlux Boot Starter:

<dependency>
    <groupId>org.springframework.ai</groupId>
    <artifactId>spring-ai-mcp-server-webflux-spring-boot-starter</artifactId>
</dependency>

This starter provides:

• Reactive transport using Spring WebFlux (WebFluxSseServerTransport)
• Auto-configured reactive SSE endpoints
• Optional STDIO transport
• Included spring-boot-starter-webflux and mcp-spring-webflux dependencies

Building the Project

Build the project using Maven:

./mvnw clean install -DskipTests

Running the Server

The server supports two transport modes:

WebFlux SSE Mode (Default)

java -jar target/mcp-weather-starter-webflux-server-0.0.1-SNAPSHOT.jar

STDIO Mode

To enable STDIO transport, set the appropriate properties:

java -Dspring.ai.mcp.server.stdio=true -Dspring.main.web-application-type=none -jar target/mcp-weather-starter-webflux-server-0.0.1-SNAPSHOT.jar

Configuration

Configure the server through application.properties:

# Server identification
spring.ai.mcp.server.name=my-weather-server
spring.ai.mcp.server.version=0.0.1

# Server type (SYNC/ASYNC)
spring.ai.mcp.server.type=SYNC

# Transport configuration
spring.ai.mcp.server.stdio=false
spring.ai.mcp.server.sse-message-endpoint=/mcp/message

# Change notifications
spring.ai.mcp.server.resource-change-notification=true
spring.ai.mcp.server.tool-change-notification=true
spring.ai.mcp.server.prompt-change-notification=true

# Logging (required for STDIO transport)
spring.main.banner-mode=off
logging.file.name=./target/starter-webflux-server.log

Available Tools

Weather Forecast Tool

• Name: getWeatherForecastByLocation
• Description: Get weather forecast for a specific latitude/longitude
• Parameters:
  • latitude: double - Latitude coordinate
  • longitude: double - Longitude coordinate
• Example:

CallToolResult forecastResult = client.callTool(new CallToolRequest("getWeatherForecastByLocation",
    Map.of("latitude", 47.6062, "longitude", -122.3321)));

Weather Alerts Tool

• Name: getAlerts
• Description: Get weather alerts for a US state
• Parameters:
  • state: String - Two-letter US state code (e.g., CA, NY)
• Example:

CallToolResult alertResult = client.callTool(new CallToolRequest("getAlerts",
    Map.of("state", "NY")));

Server Implementation

The server uses Spring Boot and Spring AI's tool annotations for automatic tool registration:

@SpringBootApplication
public class McpServerApplication {
    public static void main(String[] args) {
        SpringApplication.run(McpServerApplication.class, args);
    }

    @Bean
    public List<ToolCallback> k3sTools(clusterService clusterService) {
        return List.of(ToolCallbacks.from(clusterService));
    }
}

The clusterService implements the weather tools using the @Tool annotation:

@Service
public class clusterService {
    @Tool(description = "Get weather forecast for a specific latitude/longitude")
    public String getWeatherForecastByLocation(double latitude, double longitude) {
        // Implementation using weather.gov API
    }

    @Tool(description = "Get weather alerts for a US state. Input is Two-letter US state code (e.g., CA, NY)")
    public String getAlerts(String state) {
        // Implementation using weather.gov API
    }
}

MCP Clients

You can connect to the weather server using either STDIO or SSE transport:

Manual Clients

WebFlux SSE Client

For servers using SSE transport:

var transport = new WebFluxSseClientTransport(WebClient.builder().baseUrl("http://localhost:8080"));
var client = McpClient.sync(transport).build();

STDIO Client

For servers using STDIO transport:

var stdioParams = ServerParameters.builder("java")
    .args("-Dspring.ai.mcp.server.stdio=true",
          "-Dspring.main.web-application-type=none",
          "-Dspring.main.banner-mode=off",
          "-Dlogging.pattern.console=",
          "-jar",
          "target/mcp-weather-starter-webflux-server-0.0.1-SNAPSHOT.jar")
    .build();

var transport = new StdioClientTransport(stdioParams);
var client = McpClient.sync(transport).build();

The sample project includes example client implementations:

• SampleClient.java: Manual MCP client implementation
• ClientStdio.java: STDIO transport connection
• ClientSse.java: SSE transport connection

For a better development experience, consider using the MCP Client Boot Starters. These starters enable auto-configuration of multiple STDIO and/or SSE connections to MCP servers. See the starter-default-client and starter-webflux-client projects for examples.

Boot Starter Clients

Lets use the starter-webflux-client client to connect to our weather starter-webflux-server.

Follow the starter-webflux-client readme instruction to build a mcp-starter-webflux-client-0.0.1-SNAPSHOT.jar client application.

STDIO Transport

1. Create a mcp-servers-config.json configuration file with this content:

{
  "mcpServers": {
    "weather-starter-webflux-server": {
      "command": "java",
      "args": [
        "-Dspring.ai.mcp.server.stdio=true",
        "-Dspring.main.web-application-type=none",
        "-Dlogging.pattern.console=",
        "-jar",
        "/absolute/path/to/mcp-weather-starter-webflux-server-0.0.1-SNAPSHOT.jar"
      ]
    }
  }
}

2. Run the client using the configuration file:

java -Dspring.ai.mcp.client.stdio.servers-configuration=file:mcp-servers-config.json \
 -Dai.user.input='What is the weather in NY?' \
 -Dlogging.pattern.console= \
 -jar mcp-starter-webflux-client-0.0.1-SNAPSHOT.jar

SSE (WebFlux) Transport

1. Start the mcp-weather-starter-webflux-server:

java -jar mcp-weather-starter-webflux-server-0.0.1-SNAPSHOT.jar

starts the MCP server on port 8080.

2. In another console start the client configured with SSE transport:

java -Dspring.ai.mcp.client.sse.connections.weather-server.url=http://localhost:8080 \
 -Dlogging.pattern.console= \
 -Dai.user.input='What is the weather in NY?' \
 -jar mcp-starter-webflux-client-0.0.1-SNAPSHOT.jar

Additional Resources

• Spring AI Documentation
• MCP Server Boot Starter
• MCP Client Boot Starter
• Model Context Protocol Specification
• Spring Boot Auto-configuration

{
  "servers": {
    "weather-starter-webflux-server": {
      "type": "http",
      "url": "http://localhost:8080/mcp"
    }
  }
}

amanhogan@Amans-MacBook-Air k3s-mcp % npx @modelcontextprotocol/inspector