Spring AI Resos

Provides an MCP server to connect a Spring AI enhanced restaurant booking system with an API-first approach.

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6 months ago

First Indexed

2 months ago

Catalog Refreshed

Documentation & install

Readme and setup notes from the catalogue, plus a client-ready config you can copy for your MCP host.

Installation

Add the following to your MCP client configuration file.

Configuration

View docs

{
  "mcpServers": {
    "pacphi-spring-ai-resos": {
      "command": "java",
      "args": [
        "-jar",
        "<path-to-project>/target/spring-ai-resos-mcp-server-0.0.1-SNAPSHOT.jar"
      ],
      "env": {
        "RESOS_API_ENDPOINT": "http://localhost:8080/api/v1/resos"
      }
    }
  }
}

You can run the MCP server for the Spring AI Enhanced Restaurant Booking System to enable chat-based restaurant search and reservations via an MCP client. This server bridges the chatbot client with the ResOs API and the Spring AI backend, letting you operate end-to-end workflows from natural language prompts to reservations.

How to use

Interact with the MCP server through a compatible client (such as the Claude Desktop integration or the chatbot UI) to search for restaurants and place reservations using natural language.

Run the MCP server locally and point your client at it. You can enable different AI providers and configurations by starting the server with the appropriate profiles. The server exposes endpoints and tooling that your MCP client can call to perform actions like querying restaurants, checking availability, and creating reservations.

How to install

Prerequisites you need before installing and running: Java Development Kit (JDK 21 or newer), Maven (3.9.11 or newer), Git, and a terminal/shell. You may also want an LLM provider account (OpenAI, Groq Cloud, or OpenRouter) if you plan to use public cloud models.

Clone the project to your local machine using either Git or GitHub CLI.

# Clone the project
git clone https://github.com/pacphi/spring-ai-resos

# Or using GitHub CLI
gh repo clone pacphi/spring-ai-resos

# Build the project
cd spring-ai-resos
mvn clean install

Run the MCP server and backend

Start the backend and then the MCP server to enable the chatbot flow.

# Start the backend module (dev profile)
cd backend
mvn clean spring-boot:run -Dspring-boot.run.profiles=dev -Dspring-boot.run.jvmArguments="--add-opens java.base/java.net=ALL-UNNAMED"

# Start the MCP server (stdio)
cd ../mcp-server
export RESOS_API_ENDPOINT=http://localhost:8080/api/v1/resos
mvn spring-boot:run -Dspring-boot.run.profiles=cloud,dev