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

Data sources -> Loki -> Explore

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.