LLM SSE MCP Demo

by nlinhvu

14 stars

176 downloads

Not rated

GitHub

About

This project demonstrates the integration between LLM clients and MCP (Model Context Protocol) servers using Server-Sent Events (SSE) for real-time communication.

Details

Author: nlinhvu
GitHub stars: 14
Downloads: 176
Categories: AI

- OAuth 2.0 authorization for MCP services
- Mathematical tools: addition and multiplication
- Date/time tools: current time and alarm setting
- SSE-based real-time client-server communication
- Multi-provider LLM support (Claude, GPT, Gemini, Ollama)
- Integrated observability with Grafana, Prometheus, Tempo, Loki

Setting up with Highlight

This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:

Download and install Highlight from highlightai.com/download
Navigate to the plugins tab and select "Add Custom Plugin"
Configure the plugin with the settings below

Plugin Name LLM SSE MCP Demo

Command (node, npx, python, etc.)

Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.
Enable "Start Automatically" if you want the plugin to start when Highlight launches

Setting up with Cursor

Open Cursor's settings
Navigate to the MCP section
Click "Add new Global MCP server"
Copy and paste the configuration below based on your operating system

JSON

{
    "mcpServers": {
        "llm sse mcp demo": {
            "llm-sse-mcp-demo-2025": {
                "command": "docker",
                "args": [
                    "compose",
                    "up",
                    "-d"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "llm sse mcp demo": {
            "llm-sse-mcp-demo-2025": {
                "command": "docker",
                "args": [
                    "compose",
                    "up",
                    "-d"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "llm sse mcp demo": {
            "llm-sse-mcp-demo-2025": {
                "command": "docker",
                "args": [
                    "compose",
                    "up",
                    "-d"
                ]
            }
        }
    }
}

Setting up with Claude Desktop

Open Claude Desktop's settings
Go to the Integrations tab
Click "Add MCP Server"
Use the configuration below based on your operating system

Note: Make sure Claude Desktop is running before attempting to connect.

JSON

{
    "mcpServers": {
        "llm sse mcp demo": {
            "llm-sse-mcp-demo-2025": {
                "command": "docker",
                "args": [
                    "compose",
                    "up",
                    "-d"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "llm sse mcp demo": {
            "llm-sse-mcp-demo-2025": {
                "command": "docker",
                "args": [
                    "compose",
                    "up",
                    "-d"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "llm sse mcp demo": {
            "llm-sse-mcp-demo-2025": {
                "command": "docker",
                "args": [
                    "compose",
                    "up",
                    "-d"
                ]
            }
        }
    }
}

Setting up with Windsurf

Open Windsurf's preferences
Go to the Integrations section
Click "Add MCP Integration"
Use the configuration below based on your operating system

JSON

{
    "mcpServers": {
        "llm sse mcp demo": {
            "llm-sse-mcp-demo-2025": {
                "command": "docker",
                "args": [
                    "compose",
                    "up",
                    "-d"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "llm sse mcp demo": {
            "llm-sse-mcp-demo-2025": {
                "command": "docker",
                "args": [
                    "compose",
                    "up",
                    "-d"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "llm sse mcp demo": {
            "llm-sse-mcp-demo-2025": {
                "command": "docker",
                "args": [
                    "compose",
                    "up",
                    "-d"
                ]
            }
        }
    }
}

Setting up with Cline

Open Cline's settings
Navigate to the Integrations section
Click "Add MCP Server"
Copy and paste the configuration below based on your operating system

Note: Make sure to restart Cline after adding the configuration.

JSON

{
    "mcpServers": {
        "llm sse mcp demo": {
            "llm-sse-mcp-demo-2025": {
                "command": "docker",
                "args": [
                    "compose",
                    "up",
                    "-d"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "llm sse mcp demo": {
            "llm-sse-mcp-demo-2025": {
                "command": "docker",
                "args": [
                    "compose",
                    "up",
                    "-d"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "llm sse mcp demo": {
            "llm-sse-mcp-demo-2025": {
                "command": "docker",
                "args": [
                    "compose",
                    "up",
                    "-d"
                ]
            }
        }
    }
}

Setting up with Goose

Open Goose's preferences
Go to the Integrations tab
Select "MCP Servers"
Click "Add New Server"
Use the configuration below based on your operating system

JSON

{
    "mcpServers": {
        "llm sse mcp demo": {
            "llm-sse-mcp-demo-2025": {
                "command": "docker",
                "args": [
                    "compose",
                    "up",
                    "-d"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "llm sse mcp demo": {
            "llm-sse-mcp-demo-2025": {
                "command": "docker",
                "args": [
                    "compose",
                    "up",
                    "-d"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "llm sse mcp demo": {
            "llm-sse-mcp-demo-2025": {
                "command": "docker",
                "args": [
                    "compose",
                    "up",
                    "-d"
                ]
            }
        }
    }
}

From the repository

Start the observability stack (Prometheus, Tempo, Loki, Grafana) with Docker Compose, then run each Spring Boot app via ./gradlew bootRun in order: authorization server (port 9000), MCP server (port 8080), LLM client (port 10101). Set environment variables for cloud LLM API keys as needed. Open a browser to http://localhost:10101 to send queries like math operations or time requests.

Claude Desktop / Cursor

Paste into your MCP client config file to install this server.

{
    "mcpServers": {
        "llm sse mcp demo": {
            "llm-sse-mcp-demo-2025": {
                "command": "docker",
                "args": [
                    "compose",
                    "up",
                    "-d"
                ]
            }
        }
    }
}

McpServers

{
    "llm-sse-mcp-demo-2025": {
        "command": "docker",
        "args": [
            "compose",
            "up",
            "-d"
        ]
    }
}

LLM SSE MCP with Observability (Prometheus/Metrics, Tempo/Traces, Loki/Logs, Grafana)

This project demonstrates the integration between LLM clients and MCP (Model Context Protocol) servers using Server-Sent Events (SSE) for real-time communication. It consists of three Spring Boot applications that showcase OAuth 2.0 security, tool calling capabilities with various LLM models, and secure authentication services.

Project Structure

1. Authorization Server Demo (`authorization-server-demo`)

A Spring Boot application that implements OAuth 2.0 authorization server functionality, providing secure authentication and authorization services.

Features:
- OAuth 2.0 Authorization Server: Issues access tokens and validates them

Port: 9000

2. SSE MCP Server Demo (`sse-mcp-server-demo`)

A Spring Boot application that serves as an MCP server, exposing mathematical and date/time tools via SSE endpoints.

Features:
- Math Tools: Addition and multiplication operations
- DateTime Tools: Current time retrieval and alarm setting
- SSE Support: Real-time communication via Server-Sent Events
- MCP Protocol: Implements Model Context Protocol for tool discovery and execution

Available Tools:
- sumNumbers(int, int) - Adds two numbers
- multiplyNumbers(int, int) - Multiplies two numbers
- getCurrentDateTime() - Gets current date/time in user's timezone
- setAlarm(String) - Sets an alarm for specified ISO-8601 time

Port: 8080 (default)

3. LLM MCP Client Demo (`llm-mcp-client-demo`)

A Spring Boot web application that connects to the MCP server and provides an interactive chat interface with multiple LLM providers.

Features:
- Multiple LLM Support: Anthropic Claude, OpenAI GPT, Google Gemini, Ollama
- Interactive Web Chat: Real-time chat interface using Thymeleaf
- MCP Integration: Connects to SSE MCP server for tool calling
- Tool Discovery: Automatically discovers and uses available tools from MCP server

Supported LLM Models:
- Anthropic Claude: claude-sonnet-4-20250514
- OpenAI: o4-mini-2025-04-16
- Google Gemini: gemini-2.5-flash-preview-05-20
- Ollama: qwen3:8b (local)

Port: 10101

Prerequisites

- Java 17 or higher
- Gradle
- API keys for cloud LLM providers (optional)
- Ollama installed locally (for local models)
- Docker & Docker Compose

Environment Variables

For the LLM client, set the following environment variables for cloud providers:

export ANTHROPIC_API_KEY=your_anthropic_key
export OPENAI_API_KEY=your_openai_key
export GOOGLE_PROJECT_ID=your_google_project_id
export GOOGLE_ZONE=your_google_zone

Quick Start

1. Start Prometheus, Tempo, Loki, Grafana

docker compose up -d

2. Start the Authorization Server

cd authorization-server-demo
./gradlew bootRun

3. Start the MCP Server

cd sse-mcp-server-demo
./gradlew bootRun

4. Start the LLM Client

cd llm-mcp-client-demo
./gradlew bootRun

5. Access the Chat Interface

Open your browser and navigate to: http://localhost:10101

6. Access Grafana and explore Prometheus, Tempo, Loki

Open your browser and navigate to: http://localhost:3000

> Data sources -> Prometheus -> Explore

> Data sources -> Tempo -> Explore
tempo

> Data sources -> Loki -> Explore
loki

Usage

1. Start both services in the order specified above
2. Open the web interface at http://localhost:9090
3. Send messages that require mathematical operations or time queries
4. Watch the LLM automatically discover and use the available tools

Example queries:
- "What's 5 times 4 plus 7?"
- "What time is it?"
- "Set an alarm for 2025-01-01T10:00:00"

Technology Stack

- Spring Boot 3.x
- Spring Security OAuth2
- Spring AI - LLM integration framework
- Model Context Protocol (MCP) - Tool discovery and execution
- Server-Sent Events (SSE) - Real-time communication
- Thymeleaf - Web templating
- Gradle - Build system

Configuration

All applications use YAML configuration files:
- Authorization server configuration in authorization-server-demo/src/main/resources/application.yml
- MCP server configuration in sse-mcp-server-demo/src/main/resources/application.yml
- LLM client configuration in llm-mcp-client-demo/src/main/resources/application.yml

Development

The project demonstrates:
- MCP Protocol Implementation using Spring AI
- SSE-based Real-time Communication
- Multi-provider LLM Integration
- Tool Calling and Discovery
- Interactive Web Interfaces
- MCP Authorization with OAuth2
- Observation with Spring Actuator and Micrometer(OpenTelemetry, Prometheus, Tempo, Loki, Grafana)

This demo serves as a foundation for building more complex LLM-powered applications with external tool capabilities.

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About

Details

Jump to

Setting up with Highlight

From the repository

Claude Desktop / Cursor

McpServers

LLM SSE MCP with Observability (Prometheus/Metrics, Tempo/Traces, Loki/Logs, Grafana)

Project Structure

1. Authorization Server Demo (authorization-server-demo)

2. SSE MCP Server Demo (sse-mcp-server-demo)

3. LLM MCP Client Demo (llm-mcp-client-demo)

Prerequisites

Environment Variables

Quick Start

1. Start Prometheus, Tempo, Loki, Grafana

2. Start the Authorization Server

3. Start the MCP Server

4. Start the LLM Client

5. Access the Chat Interface

6. Access Grafana and explore Prometheus, Tempo, Loki

Usage

Technology Stack

Configuration

Development

Install

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1. Authorization Server Demo (`authorization-server-demo`)

2. SSE MCP Server Demo (`sse-mcp-server-demo`)

3. LLM MCP Client Demo (`llm-mcp-client-demo`)