This project demonstrates how to use the Spring AI MCP (Model Context Protocol) Client Boot Starter in a Spring Boot application. It showcases how to connect to MCP servers and integrate them with Spring AI's tool execution framework.
Follow the MCP Client Boot Starter reference documentation.
The project uses Spring Boot and Spring AI to create a command-line application that demonstrates MCP server integration. The application:
- Connects to MCP servers using STDIO and/or SSE (HttpClient-based) transports
- Integrates with Spring AI's chat capabilities
- Demonstrates tool execution through MCP servers
- Takes a user-defined question via the
-Dai.user.input
command-line property, which is mapped to a Spring@Value
annotation in the code
For example, running the application with -Dai.user.input="Does Spring AI support MCP?"
will inject this question into the application through Spring's property injection, and the application will use it to query the MCP server.
- Java 17 or later
- Maven 3.6+
- Anthropic API key (Claude) (Get one at https://docs.anthropic.com/en/docs/initial-setup)
- Brave Search API key (Get one at https://brave.com/search/api/)
The project uses the following main dependencies:
<dependencies>
<dependency>
<groupId>org.springframework.ai</groupId>
<artifactId>spring-ai-starter-mcp-client</artifactId>
</dependency>
<dependency>
<groupId>org.springframework.ai</groupId>
<artifactId>spring-ai-starter-model-anthropic</artifactId>
</dependency>
</dependencies>
Check the MCP Client configuration properties documentation.
The application can be configured through application.properties
or application.yml
:
# Application Configuration
spring.application.name=mcp
spring.main.web-application-type=none
# AI Provider Configuration
spring.ai.anthropic.api-key=${ANTHROPIC_API_KEY}
Follow the STDIO Configuration properties documentation.
Configure a separate, named configuration for each STDIO server you connect to:
spring.ai.mcp.client.stdio.connections.brave-search.command=npx
spring.ai.mcp.client.stdio.connections.brave-search.args=-y,@modelcontextprotocol/server-brave-search
Here, brave-search
is the name of your connection.
Alternatively, you can configure STDIO connections using an external JSON file in the Claude Desktop format:
spring.ai.mcp.client.stdio.servers-configuration=classpath:/mcp-servers-config.json
Example mcp-servers-config.json
:
{
"mcpServers": {
"brave-search": {
"command": "npx",
"args": [
"-y",
"@modelcontextprotocol/server-brave-search"
],
"env": {
}
}
}
}
You can also connect to Server-Sent Events (SSE) servers using HttpClient. Follow the SSE Configuration properties documentation.
The properties for SSE transport are prefixed with spring.ai.mcp.client.sse
:
spring.ai.mcp.client.sse.connections.server1.url=http://localhost:8080
spring.ai.mcp.client.sse.connections.server2.url=http://localhost:8081
The application demonstrates a simple command-line interaction with an AI model using MCP tools:
- The application starts and configures multiple MCP Clients (one for each provided STDIO or SSE connection configuration)
- It builds a ChatClient with the configured MCP tools
- Sends a predefined question (set via the
ai.user.input
property) to the AI model - Displays the AI's response
- Automatically closes the application
-
Set the required environment variable:
export ANTHROPIC_API_KEY=your-api-key export BRAVE_API_KEY='your-brave-api-key-here'
-
Build the application:
./mvnw clean install
-
Run the application:
java -Dai.user.input='Does Spring AI support MCP?' -jar target/mcp-starter-default-client-0.0.1-SNAPSHOT.jar
The application will execute the question "Does Spring AI support MCP?", use the provided brave (or other tools) to answer it, and display the AI assistant's response.