Hotpepper Gourmet MCP Server: Universal Adapter for AI Applications

Overview: What is Hotpepper Gourmet MCP Server?

The hotpepper-gourmet-mcp-server is an open-source, non-official MCP (Model Context Protocol) server that enables a wide range of AI applications like Claude Desktop, Continue, Cursor and others to connect to the popular Japanese restaurant review platform, Hotpepper Gourmet, through a standardized protocol. This server acts as a bridge between these AI tools and the rich dataset provided by Hotpepper Gourmet API, thereby enhancing their functionality and utility.

🔧 Core Features & MCP Capabilities

The hotpepper-gourmet-mcp-server supports various endpoints corresponding to the Hotpepper Gourmet Web Services APIs for enhanced AI capabilities in restaurant search, genre classification, area master data retrieval, budget estimation, service area information, and credit card acceptance details. These features are designed to provide AI applications with comprehensive context for making informed decisions or generating recommendations based on local dining options.

⚙️ MCP Architecture & Protocol Implementation

At the core of this server's architecture is a full implementation of the Model Context Protocol (MCP), which ensures seamless integration between different tools and data sources. The protocol flow diagram illustrates how MCP clients interact with the server to access Hotpepper Gourmet APIs:

graph LR
    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

By leveraging MCP, this server ensures that AI applications can reliably query and utilize data from Hotpepper Gourmet without the need for explicit API calls or manual configuration.

🚀 Getting Started with Installation

For quick setup, users can choose between various installation methods:

• Homebrew:

  brew install miyamo2/tap/hotpepper-gourmet-mcp-server
  

• Go:

  go install github.com/miyamo2/hotpepper-gourmet-mcp-server@latest
  

• Download from Release Page: Visit https://github.com/miyamo2/hotpepper-gourmet-mcp-server/releases/latest

💡 Key Use Cases in AI Workflows

Scenario 1: Restaurant Recommendation System

In an AI-driven restaurant recommendation system, clients can leverage the server to search for nearby restaurants based on user preferences. For instance, a query could be dispatched from Claude Desktop that requires detailed restaurant information within a specific budget range and area.

request = {
  "server": "hotpepper-gourmet-mcp-server",
  "action": "search_restaurants",
  "params": {
    "location": "Tokyo",
    "budget": "2000-3000",
    "genre": "Japanese"
  }
}

Scenario 2: Personalized Dieter's Guide

For a personalized nutrition and wellness application, users can provide dietary needs (e.g., calorie restrictions), and the server will return tailored restaurant suggestions that meet their requirements. Through Continue, an AI helper can ask for more details like specific dish preferences or allergy information before making recommendations.

request = {
  "server": "hotpepper-gourmet-mcp-server",
  "action": "search_restaurants",
  "params": {
    "dietary_needs": "gluten-free",
    "location": "Shinjuku"
  }
}

🔌 Integration with MCP Clients

Below is a compatibility matrix for major MCP clients:

MCP Client	Resources	Tools	Prompts	Status
Claude Desktop	✅	✅	✅	Full Support
Continue	✅	✅	✅	Full Support
Cursor	❌	✅	❌	Tools Only

Support for certain clients in the "Prompts" column suggests that while the core functionalities are available, some features like personalized queries might require additional configuration or adaptations.

📊 Performance & Compatibility Matrix

The server is designed to handle a wide variety of tasks efficiently. Users can configure it via settings and environment variables to adapt to different requirements. For instance, setting up the mcpServer section for Hotpepper Gourmet involves specifying an API key:

{
  "mcpServers": {
    "hotpepper-gourmet-mcp-server": {
      "command": "hotpepper-gourmet-mcp-server",
      "args": [],
      "env": {
        "HOTPEPPER_GOURMET_API_KEY": "<Hotpepper Gourmet API Key>"
      }
    }
  }
}

Ensure that the HOTPEPPER_GOURMET_API_KEY is correctly replaced with your own key.

🛠️ Advanced Configuration & Security

Advanced users can fine-tune server behavior and security settings by manipulating command-line arguments and environment variables. This flexibility allows for secure data handling and improved performance tailored to specific needs. Detailed configuration options are documented in the official MCP documentation, which should be consulted for an exhaustive guide.

❓ Frequently Asked Questions (FAQ)

1. Q: Can I use this server with any AI application?

   • A: While this is a non-official MCP server, it is compatible with many popular AI applications like those listed in the compatibility matrix.

2. Q: How secure is the API key when configuring the server?

   • A: The API key should be kept confidential and stored securely to prevent unauthorized access.

3. Q: Are there any restrictions on the number of requests per minute?

   • A: There are no explicit rate limits set by default, but users may need to implement their own throttling mechanisms based on service-level requirements.

4. Q: Can I customize responses from Hotpepper Gourmet based on user preferences?

   • A: Yes, you can pass custom parameters in your requests to filter or modify the data retrieved, aligning with user-specific criteria.

5. Q: How do I troubleshoot compatibility issues between clients and this server?

   • A: If a client does not support certain features (indicated in the compatibility matrix), check if it is possible to update client software versions or configurations to enable full feature compatibility.

👨‍💻 Development & Contribution Guidelines

Contributions are welcome! Developers interested in enhancing the functionality, improving documentation, or adding new tools can follow the contributing guidelines available on GitHub. Issues and pull requests should be submitted as per the repository's conventions to help maintain a high standard of quality and utility.

🌐 MCP Ecosystem & Resources

For more information about the broader MCP ecosystem and integration resources, refer to the official Model Context Protocol documentation and community forums. Engaging with the larger developer community can offer additional support and insights into best practices when integrating MCP solutions.

By enabling AI applications to access real-world data seamlessly, this hotpepper-gourmet-mcp-server represents a significant step in enhancing the intelligence and accuracy of modern AI tools within specific contexts like food and local services.