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Add docs for the mcp/client-starter projects

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Signed-off-by: Christian Tzolov <christian.tzolov@broadcom.com>
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Christian Tzolov
2025-02-10 08:41:53 +01:00
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# Spring AI - MCP Starter Client
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](https://docs.spring.io/spring-ai/reference/api/mcp/mcp-client-boot-starter-docs.html) reference documentation.
## Overview
The project uses Spring Boot and Spring AI to create a command-line application that:
- 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
## Prerequisites
- Java 17 or later
- Maven 3.6+
- Anthropic API key (for Claude AI model)
## Dependencies
The project uses the following main dependencies:
```xml
<dependencies>
<dependency>
<groupId>org.springframework.ai</groupId>
<artifactId>spring-ai-mcp-client-spring-boot-starter</artifactId>
</dependency>
<dependency>
<groupId>org.springframework.ai</groupId>
<artifactId>spring-ai-anthropic-spring-boot-starter</artifactId>
</dependency>
</dependencies>
```
## Configuration
### Application Properties
Check the [MCP Client configuration properties](https://docs.spring.io/spring-ai/reference/api/mcp/mcp-client-boot-starter-docs.html#_configuration_properties) documentation.
The application can be configured through `application.properties` or `application.yml`:
#### Common Properties
```properties
# Application Configuration
spring.application.name=mcp
spring.main.web-application-type=none
# AI Provider Configuration
spring.ai.anthropic.api-key=${ANTHROPIC_API_KEY}
```
#### STDIO Transport Properties
Follow the [STDIO Configuration properties](https://docs.spring.io/spring-ai/reference/api/mcp/mcp-client-boot-starter-docs.html#_stdio_transport_properties) documentation.
Configure a separate, named configuration for each STDIO server you connect to:
```properties
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:
```properties
spring.ai.mcp.client.stdio.servers-configuration=classpath:/mcp-servers-config.json
```
Example `mcp-servers-config.json`:
```json
{
"mcpServers": {
"brave-search": {
"command": "npx",
"args": [
"-y",
"@modelcontextprotocol/server-brave-search"
],
"env": {
}
}
}
}
```
#### SSE Transport Properties
You can also connect to Server-Sent Events (SSE) servers using HttpClient.
Follow the [SSE Configuration properties](https://docs.spring.io/spring-ai/reference/api/mcp/mcp-client-boot-starter-docs.html#_sse_transport_properties) documentation.
The properties for SSE transport are prefixed with `spring.ai.mcp.client.sse`:
```properties
spring.ai.mcp.client.sse.connections.server1.url=http://localhost:8080
spring.ai.mcp.client.sse.connections.server2.url=http://localhost:8081
```
## How It Works
The application demonstrates a simple command-line interaction with an AI model using MCP tools:
1. The application starts and configures multiple MCP Clients (one for each provided STDIO or SSE connection configuration)
2. It builds a ChatClient with the configured MCP tools
3. Sends a predefined question (set vi the `ai.user.input` property) to the AI model
4. Displays the AI's response
5. Automatically closes the application
## Running the Application
1. Set the required environment variable:
```bash
export ANTHROPIC_API_KEY=your-api-key
```
2. Build the application:
```bash
./mvnw clean install
```
3. Run the application:
```bash
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.
## Additional Resources
- [Spring AI Documentation](https://docs.spring.io/spring-ai/reference/)
- [MCP Client Boot Starter](https://docs.spring.io/spring-ai/reference/api/mcp/mcp-client-boot-starter-docs.html)
- [Model Context Protocol Specification](https://modelcontextprotocol.github.io/specification/)
- [Spring Boot Documentation](https://docs.spring.io/spring-boot/docs/current/reference/html/)

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model-context-protocol/client-starter/starter-default-client/src/main/java/org/springframework/ai/mcp/samples/client/Application.java
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@@ -33,7 +33,7 @@ public class Application {
SpringApplication.run(Application.class, args);
}
@Value("${spring.ai.mcp.client.demo.user.input}")
@Value("${ai.user.input}")
private String userInput;
@Bean

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@@ -11,4 +11,4 @@ spring.ai.mcp.client.stdio.connections.brave-search.args=-y,@modelcontextprotoco
# spring.ai.mcp.client.stdio.connections.brave-search.env.FOO=BAAR
spring.ai.mcp.client.demo.user.input=What tools are available?
ai.user.input=What tools are available?

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# Spring AI - MCP Starter WebFlux Client
This project demonstrates how to use the Spring AI MCP (Model Context Protocol) Client Boot Starter with WebFlux 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](https://docs.spring.io/spring-ai/reference/api/mcp/mcp-client-boot-starter-docs.html) reference documentation.
## Overview
The project uses Spring Boot and Spring AI to create a command-line application that:
- Connects to MCP servers using STDIO and/or SSE (WebFlux-based) transports
- Integrates with Spring AI's chat capabilities
- Demonstrates tool execution through MCP servers
## Prerequisites
- Java 17 or later
- Maven 3.6+
- Anthropic API key (for Claude AI model)
## Dependencies
The project uses the following main dependencies:
```xml
<dependencies>
<dependency>
<groupId>org.springframework.ai</groupId>
<artifactId>spring-ai-mcp-client-webflux-spring-boot-starter</artifactId>
</dependency>
<dependency>
<groupId>org.springframework.ai</groupId>
<artifactId>spring-ai-anthropic-spring-boot-starter</artifactId>
</dependency>
</dependencies>
```
## Configuration
### Application Properties
Check the [MCP Client configuration properties](https://docs.spring.io/spring-ai/reference/api/mcp/mcp-client-boot-starter-docs.html#_configuration_properties) documentation.
The application can be configured through `application.properties` or `application.yml`:
#### Common Properties
```properties
# Application Configuration
spring.application.name=mcp
spring.main.web-application-type=none
# AI Provider Configuration
spring.ai.anthropic.api-key=${ANTHROPIC_API_KEY}
```
#### STDIO Transport Properties
Follow the [STDIO Configuration properties](https://docs.spring.io/spring-ai/reference/api/mcp/mcp-client-boot-starter-docs.html#_stdio_transport_properties) documentation.
Configure a separate, named configuration for each STDIO server you connect to:
```properties
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:
```properties
spring.ai.mcp.client.stdio.servers-configuration=classpath:/mcp-servers-config.json
```
Example `mcp-servers-config.json`:
```json
{
"mcpServers": {
"brave-search": {
"command": "npx",
"args": [
"-y",
"@modelcontextprotocol/server-brave-search"
],
"env": {
}
}
}
}
```
#### SSE Transport Properties
You can also connect to Server-Sent Events (SSE) servers using WebFlux.
Follow the [SSE Configuration properties](https://docs.spring.io/spring-ai/reference/api/mcp/mcp-client-boot-starter-docs.html#_sse_transport_properties) documentation.
The properties for SSE transport are prefixed with `spring.ai.mcp.client.sse`:
```properties
spring.ai.mcp.client.sse.connections.server1.url=http://localhost:8080
spring.ai.mcp.client.sse.connections.server2.url=http://localhost:8081
```
## How It Works
The application demonstrates a simple command-line interaction with an AI model using MCP tools:
1. The application starts and configures multiple MCP Clients (one for each provided STDIO or SSE connection configuration)
2. It builds a ChatClient with the configured MCP tools
3. Sends a predefined question (set vi the `ai.user.input` property) to the AI model
4. Displays the AI's response
5. Automatically closes the application
## Running the Application
1. Set the required environment variable:
```bash
export ANTHROPIC_API_KEY=your-api-key
```
2. Build the application:
```bash
./mvnw clean install
```
3. Run the application:
```bash
java -Dai.user.input='Does Spring AI support MCP?' -jar target/mcp-starter-webflux-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.
## Additional Resources
- [Spring AI Documentation](https://docs.spring.io/spring-ai/reference/)
- [MCP Client Boot Starter](https://docs.spring.io/spring-ai/reference/api/mcp/mcp-client-boot-starter-docs.html)
- [Model Context Protocol Specification](https://modelcontextprotocol.github.io/specification/)
- [Spring Boot Documentation](https://docs.spring.io/spring-boot/docs/current/reference/html/)

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

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@@ -33,7 +33,7 @@ public class Application {
SpringApplication.run(Application.class, args);
}
@Value("${spring.ai.mcp.client.demo.user.input}")
@Value("${ai.user.input}")
private String userInput;
@Bean

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@@ -11,4 +11,4 @@ spring.ai.mcp.client.stdio.connections.brave-search.args=-y,@modelcontextprotoco
# spring.ai.mcp.client.stdio.connections.brave-search.env.FOO=BAAR
spring.ai.mcp.client.demo.user.input=What tools are available?
ai.user.input=What tools are available?

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model-context-protocol/client-starter/starter-webflux-client/src/main/resources/test.application.yml Normal file
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spring:
application:
name: mcp
main:
web-application-type: none
ai:
openai:
api-key: ${OPENAI_API_KEY}
anthropic:
api-key: ${ANTHROPIC_API_KEY}
mcp:
client:
stdio:
servers-configuration: classpath:/mcp-servers-config.json
ai.user.input=Does Srping AI support MCP?