TfNSW Realtime Alerts MCP Server: Integrating Transport Data into AI Workflows

Overview: What is TfNSW Realtime Alerts MCP Server?

The TfNSW Realtime Alerts MCP Server is a TypeScript-based implementation designed to integrate with Transport for NSW's (TfNSW) Realtime Alerts API. This server acts as an adapter, utilizing the Model Context Protocol (MCP), to provide real-time transport alert information and tools enabling AI applications like Claude Desktop, Continue, Cursor, and others to access this critical data seamlessly.

🔧 Core Features & MCP Capabilities

The TfNSW Realtime Alerts MCP Server offers a robust set of features that enhance its value for AI applications. Key among these are the ability to list and access transport alerts via nsw-transport:// URIs, filter those alerts by various transport modes such as buses, trains, ferries, and more, and deliver plain text data ideal for integration with natural language processing models.

Resources

• Resource URI Support: The server supports resource URLs starting with nsw-transport://, providing a standardized format that AI applications can use to query and retrieve transport alerts.
• Filtering Capabilities: Users can filter transport alerts based on specific modes of transportation, allowing for granular access control and tailored information delivery.

Tools

• Retrieve Current Alerts: Via the get-transport-alerts tool, developers and AI systems can retrieve up-to-date information about current transport disruptions. This includes relevant details such as affected routes, timing periods, and detailed impact assessments.
• Structured Data Delivery: The returned data is formatted in a way that enhances readability and ease of use for AI assistants, supporting better real-time response generation.

Prompts

• Summary Generation: The transport-disruption-summary prompt generates structured summaries of current transport alerts. These summaries include embedded resources such as relevant details about disruptions, making them ideal for summarization tasks by large language models.
• AI Integration: Structured output from this server ensures that AI applications can easily interpret and utilize the data for various applications, including but not limited to real-time notifications and user guidance.

⚙️ MCP Architecture & Protocol Implementation

The implementation of the TfNSW Realtime Alerts MCP Server follows a client-server architectural pattern with strong integration hooks into the Model Context Protocol (MCP). The server is built using TypeScript and leverages Node.js for its core execution. It requires minimal setup on the client side, adhering to standard MCP protocols to facilitate seamless interaction.

Client Compatibility

The server supports compatibility with several MCP clients, including Claude Desktop, Continue, and Cursor. However, support for Continue extends only to tools and data retrieval, while both Claude Desktop and Cursor offer full support across resources, tools, and prompts.

• MCP Client Compatibility Matrix:

  MCP Client	Resources	Tools	Prompts
  Claude Desktop	✅	✅	✅
  Continue	✅	✅	❌

MCP Protocol Flow Diagram

The following Mermaid diagram illustrates the interaction flow between a typical MCP client, such as Claude Desktop, and the TfNSW Realtime Alerts MCP Server.

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

The protocol flow diagram highlights the structured way in which data is transmitted and utilized between components, demonstrating a clean and efficient interaction model.

🚀 Getting Started with Installation

To set up and start using the TfNSW Realtime Alerts MCP Server, follow these steps:

1. Authentication: Register for an API key at the TfNSW Open Data Hub.
2. Configuration: Update your claude_desktop_config.json file (MacOS) or %APPDATA%/Claude/claude_desktop_config.json (Windows) with necessary server configurations.
3. Environment Setup: Set the API key as an environment variable in your .env file:

   NSW_TRANSPORT_API_KEY="your_api_key_here"
   

4. Dependencies Installation: Install project dependencies using npm install.
5. Build and Run:

   npm run build
   

For a development environment with autorebuild, use the following command:

npm run watch

💡 Key Use Cases in AI Workflows

Implementing the TfNSW Realtime Alerts MCP Server can significantly enhance various aspects of Artificial Intelligence workflows. Here are two realistic scenarios:

Scenario 1: Real-Time Transport Disruption Notifications

Suppose an AI application, such as a customer support system, needs to provide real-time updates about transport disruptions in NSW. By integrating with the TfNSW Realtime Alerts MCP Server via the get-transport-alerts tool, this application can fetch and display current alerts in a structured format suitable for natural language processing (NLP) tools.

// Example of integration in an NLP application
const transportAlert = await getTransportAlerts({ mode: 'buses' });
console.log(transportAlert);

Scenario 2: Automated Alert Summarization

In another scenario, an AI-based travel planning assistant needs to provide concise summaries of ongoing disruptions. By leveraging the transport-disruption-summary prompt and passing structured data from the TfNSW Realtime Alerts MCP Server:

// Example integration for summary generation
const summary = await getTransportDisruptionSummary();
console.log(summary);

These use cases demonstrate how the server can be seamlessly integrated to enhance AI application functionality with real-time transportation data.

🔌 Integration with MCP Clients

The primary purpose of the TfNSW Realtime Alerts MCP Server is to facilitate seamless integration with various MCP clients. It ensures compatibility across multiple AI tools, enhancing their ability to provide accurate and timely information about NSW transport disruptions. This server is specifically designed for MCP clients such as Claude Desktop, which offers extensive support through configurations similar to those described above.

📊 Performance & Compatibility Matrix

Server Performance

• Latency: The server aims to deliver real-time data within seconds of a request.
• Scalability: The architecture supports scaling to handle high volumes of queries without degradation in performance.

MCP Client Support Overview

Tool/Service	Resource	Tools	Prompts
Claude Desktop	✅	✅	✅
Continue	✅ (Limited)	✅ (Limited)	❌

This compatibility matrix indicates the extent of support for different MCP clients, allowing users to choose the most appropriate tool based on their specific requirements.

🛠️ Advanced Configuration & Security

For advanced configuration and enhanced security, follow these best practices:

1. Environment Variables: Ensure all API keys and other sensitive information are stored securely in environment variables.
2. Localhost Only Access: To maintain security, restrict access to the MCP Server to localhost only, unless explicitly needed for cross-environment testing.
3. Security Updates: Regularly update dependencies to ensure you have the latest security patches.

Configuration Code Sample

Here’s a sample configuration snippet to add this server as an MCP resource in your local environment:

{
  "mcpServers": {
    "tfnsw-realtime-alerts": {
      "command": "npx",
      "args": ["-y", "tfnsw-realtime-alerts-mcp-server"],
      "env": {
        "NSW_TRANSPORT_API_KEY": "your_api_key_here"
      }
    }
  }
}

Replace "your_api_key_here" with your actual API key obtained from the TfNSW Open Data Hub.

❓ Frequently Asked Questions (FAQ)

Q1: How do I integrate this server with Claude Desktop?

To integrate the TfNSW Realtime Alerts MCP Server with Claude Desktop, you need to add it as an MCP resource in your configuration file. Follow the steps mentioned above for detailed instructions.

Q2: What transport modes are supported by default?

The server supports a wide range of transport modes including buses, trains, ferries, light rail, metro, NSW trains, region buses, and Sydney trains. You can configure which mode to use based on your needs.

Q3: Can I filter alerts by specific time periods or locations?

Yes, the get-transport-alerts tool supports filtering by various parameters such as transport modes and can be further customized for additional filtering criteria if required.

Q4: Is any configuration needed for production deployment?

For a production environment, consider setting up proper authentication methods and security measures to protect your API keys and ensure secure data transmission.

Q5: How often is the data refreshed in the server?

Data from the TfNSW Realtime Alerts API is regularly updated to reflect current transport conditions. The exact refresh rate may vary depending on network latency and API response times, but updates are generally provided within minutes of change notifications.

👨‍💻 Development & Contribution Guidelines

Contributions to enhance the functionality or improve the documentation of the TfNSW Realtime Alerts MCP Server are welcomed. To contribute:

1. Fork the Repository: Visit the GitHub repository and fork it to your own account.
2. Create a Branch: Develop new features in a separate branch off main.
3. Commit Changes: Ensure all changes adhere to coding standards.
4. Pull Request: Submit a pull request for review.

🌐 MCP Ecosystem & Resources

The TfNSW Realtime Alerts MCP Server is part of the broader Model Context Protocol (MCP) ecosystem, which includes various adaptors and servers designed to connect diverse data sources to AI applications. Explore more resources on the MCP GitHub page for a comprehensive list.

By following these guidelines and integrating with this MCP server, developers can tap into real-time transport information, significantly improving the capabilities of their AI applications in NSW.