Spring AI MCP Weather Server
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Spring AI MCP Weather Serverget weather forecast for latitude 37.7749 and longitude -122.4194"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
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-starterSupport for both SSE (Server-Sent Events) and STDIO transports
Automatic tool registration using Spring AI's
@ToolannotationTwo weather-related tools:
Get weather forecast by location (latitude/longitude)
Get weather alerts by US state
Related MCP server: Weather MCP Server
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-webfluxandmcp-spring-webfluxdependencies
Building the Project
Build the project using Maven:
./mvnw clean install -DskipTestsRunning the Server
The server supports two transport modes:
WebFlux SSE Mode (Default)
java -jar target/mcp-weather-starter-webflux-server-0.0.1-SNAPSHOT.jarSTDIO 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.jarConfiguration
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.logAvailable Tools
Weather Forecast Tool
Name:
getWeatherForecastByLocationDescription: Get weather forecast for a specific latitude/longitude
Parameters:
latitude: double - Latitude coordinatelongitude: double - Longitude coordinate
Example:
CallToolResult forecastResult = client.callTool(new CallToolRequest("getWeatherForecastByLocation",
Map.of("latitude", 47.6062, "longitude", -122.3321)));Weather Alerts Tool
Name:
getAlertsDescription: 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
Create a
mcp-servers-config.jsonconfiguration 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"
]
}
}
}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.jarSSE (WebFlux) Transport
Start the
mcp-weather-starter-webflux-server:
java -jar mcp-weather-starter-webflux-server-0.0.1-SNAPSHOT.jarstarts the MCP server on port 8080.
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.jarAdditional Resources
{
"servers": {
"weather-starter-webflux-server": {
"type": "http",
"url": "http://localhost:8080/mcp"
}
}
}amanhogan@Amans-MacBook-Air k3s-mcp % npx @modelcontextprotocol/inspector
This server cannot be installed
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