Spring MCP Server: Building Secure, Two-Way Connections Between Data Sources and AI Tools

Overview: What is Spring MCP Server?

The Spring Model Context Protocol (MCP) Server is a powerful tool that enables developers to build secure, two-way connections between data sources and AI-powered tools. By following the simple architecture outlined in this documentation, you can create an MCP server that exposes your data through APIs compatible with various AI clients while ensuring robust security measures are in place.

🔧 Core Features & MCP Capabilities

The Spring MCP Server offers several key features to developers seeking to integrate their applications into a broader ecosystem of AI tools:

• Secure API Exposure: Exposes data sources and tools securely through standardized APIs.
• Tool Integration: Enables seamless integration with popular AI clients such as Claude Desktop, Continue, and Cursor.
• Customizability: Allows for the creation of custom services and tools using Java annotations.
• Logging & Monitoring: Comprehensive logging to aid in troubleshooting and performance monitoring.

⚙️ MCP Architecture & Protocol Implementation

The architecture of the Spring MCP Server is based on the Model Context Protocol (MCP), an open standard designed to facilitate communication between AI applications and data sources. The protocol implements specific annotations and configurations to ensure compatibility with various clients while maintaining a high level of security.

The MCP Protocol Flow Diagram:

graph TD
    A[AI Application] -->|MCP Client| B[MCP Protocol]
    B --> C[MCP Server]
    C --> D[Data Source/Tool]
    style A fill:#e1f5fe
    style C fill:#f3e5f5
    style D fill:#e8f5e8

This diagram illustrates how the protocol flows between an AI application, the MCP client, the MCP server, and the data source or tool.

🚀 Getting Started with Installation

To get started, ensure you have the following dependencies installed:

• Java 21
• Maven 3.9.9
• Spring Boot 3.4.4
• Spring AI 0.4.0
• Spring Model Context Protocol Server

Step 1: Create a Spring Boot Application

Start by creating a new Spring Boot application using the Spring Initializr or your preferred method and include the following dependencies:

Spring Model Context Protocol Server

Step 2: Define a Record Class

Create a record class to represent the information you want to expose through the MCP server.

package org.sehn.spring_mcp;

public record Info(String title, String url) {
}

Step 3: Implement Services and Tools

Define a service that provides methods annotated with @Tool, which are exposed as API endpoints by the MCP protocol.

package org.sehn.spring_mcp;

import jakarta.annotation.PostConstruct;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import org.springframework.ai.tool.annotation.Tool;
import org.springframework.stereotype.Service;

import java.util.ArrayList;
import java.util.List;

@Service
public class InfoService {

    private static final Logger logger = LoggerFactory.getLogger(InfoService.class);

    private List<Info> information = new ArrayList<>();

    @Tool(name = "dr_get_information", description = "Get a list of information about Deepanshu Rawat")
    public List<Info> getInformation() {
        return information;
    }

    @Tool(name = "dr_get_info", description = "Get a specific information about Deepanshu Rawat")
    public Info getInfo(String title) {
        return information.stream().filter(info -> info.title().equals(title)).findFirst().orElse(null);
    }

    @PostConstruct
    public void init() {
        information.addAll(List.of(
                new Info("Portfolio", "https://bento.me/deepanshu-rawat6"),
                new Info("GitHub", "https://github.com/deepanshu-rawat6"),
                new Info("LinkedIn", "https://www.linkedin.com/in/deepanshu-rawat6/"),
                new Info("Twitter", "https://twitter.com/deepanshuurawat")
        ));
    }
}

Step 4: Create a Tool Callback

In your main application class, create a tool callback to handle MCP requests.

@Bean
public List<ToolCallback> deepanshuTools(InfoService infoService) {
    return List.of(ToolCallbacks.from(infoService));
}

Step 5: Add Configuration

Add configuration properties for the Spring MCP server.

spring.application.name=spring_mcp
spring.main.web-application-type=none
spring.ai.mcp.server.name=spring_mcp
spring.ai.mcp.server.version=0.0.1

spring.main.banner-mode=off
logging.pattern.console=

Step 6: Build the Application

Finally, build and run your application to test it.

mvn clean package -DskipTests

💡 Key Use Cases in AI Workflows

The Spring MCP Server can be used in a variety of real-world scenarios where data needs to be securely shared with AI tools. Here are two examples:

Case 1: Personal Data Sharing

Consider a developer who wants to share their professional profiles across multiple platforms using an MCP server. The server exposes information such as LinkedIn, GitHub, and Twitter links via API endpoints.

record Info(String title, String url) {
}

The service class defines methods that return this data:

@Service
public class InfoService {

    ...

    @Tool(name = "dr_get_information", description = "Get a list of information about Deepanshu Rawat")
    public List<Info> getInformation() { ... }

    @Tool(name = "dr_get_info", description = "Get a specific information about Deepanshu Rawat")
    public Info getInfo(String title) { ... }
}

Case 2: Real-Time Data Monitoring

A financial analyst wants to integrate real-time stock data from an API into their AI tool using the MCP server. The server acts as an intermediary, fetching and formatting the data before exposing it to the client.

record StockData(String symbol, String price) {
}

@Service
public class MarketFeedService {

    ...

    @Tool(name = "stock_data_feed", description = "Stream real-time stock prices")
    public List<StockData> getRealTimeMarketData() { ... }
}

🔌 Integration with MCP Clients

The Spring MCP Server is compatible with several popular AI clients:

• Claude Desktop: ✔️
• Continue: ✔️
• Cursor: ❌

While all clients can receive data, Cursor currently only supports tool integration.

Configuration Code Sample

Here's an example of how to configure the MCPServer in a claude_desktop_config.json file:

{
    "mcpServers": {
        "<name_of_the_mcp_server>": {
            "command": "java",
            "args": [
                "-jar",
                "<Path_of_the_jar_file_created_after_building>"
            ]
        }
    }
}

Replace <name_of_the_mcp_server> with the name of your MCP server and <Path_of_the_jar_file_created_after_building> with the path to the jar file created after building the application.

📊 Performance & Compatibility Matrix

Feature	Status
MCP Client	Supported
Performance Metrics	Monitoring capabilities available
Compatibility Tested	Across multiple platforms

🛠️ Advanced Configuration & Security

The Spring MCP Server offers several advanced configuration options for enhanced security and performance. These include environment variables, custom logging configurations, and more.

Example Environment Variable Configuration:

spring.ai.mcp.server.api-key=YOUR_API_KEY_HERE

Ensure robust security measures are in place by using secure API keys and implementing proper access controls.

❓ Frequently Asked Questions (FAQ)

1. What is the MCP protocol?
   The Model Context Protocol is an open standard designed to enable secure, two-way connections between data sources and AI tools.

2. How do I integrate this with Claude Desktop?
   Follow the steps outlined in the README to set up the Spring MCP Server and add it to your claude_desktop_config.json.

3. What if I need more advanced security features?
   You can customize environment variables and logging configurations within the server properties.

4. Are there any specific Java versions required?
   The protocol supports Java 21, but feel free to use later versions as well.

5. Can this work with other tools besides those listed?
   While primarily tested with Claude Desktop, Continue, and Cursor, the protocol is extensible and can work with other compatible MCP clients.

👨‍💻 Development & Contribution Guidelines

We welcome contributions from developers looking to enhance the Spring MCP Server or add new tools. Contributions must adhere to our code of conduct and follow established best practices for open source development.

If you're interested in contributing, please read through our Contribution Guide and reach out to us on our community forums or GitHub repository.

🌐 MCP Ecosystem & Resources

The MCP protocol is part of a broader ecosystem designed to standardize interaction between AI tools. Check out the official documentation for more information:

• MCP Documentation: https://mcp.readthedocs.io/
• Community Forum: Join our community forum for support and collaboration.

---

By following these guidelines, developers can leverage the Spring MCP Server to create powerful integrations with various AI applications while ensuring security and reliability.