TfNSW Realtime Alerts MCP Server: Enabling Seamless Integration of Transport Alerts Data for AI Applications

Overview: What is TfNSW Realtime Alerts MCP Server?

The TfNSW Realtime Alerts MCP Server is a TypeScript-based implementation that connects AI applications to the real-time transport alerts provided by Transport for NSW (TfNSW). This server acts as an intermediary, enabling AI assistants and other applications to efficiently retrieve and process up-to-date transport information. By adhering to the Model Context Protocol (MCP), it ensures compatibility with various MCP clients like Claude Desktop, Continue, Cursor, and others, thereby enhancing their capabilities in providing accurate and timely transportation-related services.

🔧 Core Features & MCP Capabilities

The TfNSW Realtime Alerts MCP Server is designed to leverage AI technologies to offer a comprehensive solution for transport information management. Key features include:

Resources

• URIs for Transport Alerts: The server allows querying of transport alerts via nsw-transport:// URIs, making it easy for AI applications to fetch and display relevant information.
• Transport Mode Filtering: Users can filter alerts by various transport modes such as buses, trains, ferries, light rail, and metro. This filtering capability ensures that the content is relevant to specific users.

Tools

• Get Transport_alerts Command:
  • Retrieve Current Alerts: The get-transport-alerts tool fetches current transport alerts.
  • Filtering Options: Users can filter alerts by specifying the desired transport mode, enhancing the precision of the retrieved data.
  • Structured Output: The output includes detailed information about affected routes, time periods, and impact details, facilitating informed decision-making.

Prompts

• Transport Disruption Summary:
  • Summary Generation: The transport-disruption-summary prompt generates a concise summary of current transport alerts.
  • Embedded Resources: This summary embeds relevant alert details as structured resources, enabling advanced processing by large language models (LLMs).
  • Structured Prompt for LLM Summarisation: By returning a structured format, this capability supports efficient summation and summarization tasks within AI workflows.

⚙️ MCP Architecture & Protocol Implementation

MCP Protocol Flow

The MCP server interacts with the TfNSW Realtime Alerts data source through a standardized Model Context Protocol. The protocol flow can be visualized as follows:

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

MCP Data Architecture

The data architecture of the TfNSW Realtime Alerts MCP Server is structured to optimize data retrieval and processing. It involves:

• URIs for Transport Alerts: Using nsw-transport:// URIs to facilitate easy access.
• Transport Mode Definitions: Defining transport modes such as buses, trains, ferries, light rail, metro, and regional services to enable filtering and customization.

🚀 Getting Started with Installation

To utilize the TfNSW Realtime Alerts MCP Server in applications like Claude Desktop, you need to configure your environment properly. Follow these steps:

1. Configure API Key: For using this server with MCP clients, ensure you have an API key from the TfNSW Open Data Hub.

2. Add Server Configuration:

   • MacOS:

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

   • Windows:

     "%APPDATA%/Claude/claude_desktop_config.json"
     

3. Install Required Dependencies: Run the following commands to set up your development environment:

   npm install
   

4. Build and Watch for Changes:

   • For a production-ready build, run:

     npm run build
     

   • To enable auto-rebuild during development, use:

     npm run watch
     

💡 Key Use Cases in AI Workflows

Real-time Alert Monitoring for Commuters

Imagine an AI assistant that uses the TfNSW Realtime Alerts MCP Server to monitor real-time transportation disruptions. The server's get-transport-alerts tool can be integrated with a commutable app, allowing users to receive immediate notifications about bus and train delays or cancellations. This ensures commuters are always aware of any potential changes in their travel plans.

Comprehensive Disruption Summarization

For large event organizers managing public transport during festivals or major events, the server's transport-disruption-summary prompt can generate a concise summary of current disruptions. This helps event managers and planners quickly understand the impact on transportation services and make informed decisions about crowd management or alternate route planning.

🔌 Integration with MCP Clients

The TfNSW Realtime Alerts MCP Server supports several popular MCP clients, ensuring broad compatibility across different AI application environments:

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

This integration allows users of these applications to seamlessly access real-time transportation data, enhancing their capabilities in providing accurate and relevant information.

📊 Performance & Compatibility Matrix

The performance and compatibility matrix for the TfNSW Realtime Alerts MCP Server with different clients are as follows:

MCP Client	API Key	Resources	Tools	Prompts
Claude Desktop	Yes	✅	✅	✅
Continue	Yes	✅	✅	✅
Cursor	No API Key	✅	✅	❌

Compatibility Notes

• Claude Desktop: Supports all features and provides full compatibility.
• Continue: Supports all features without an API key, ensuring broad accessibility.

🛠️ Advanced Configuration & Security

To configure the server for advanced use cases, follow these steps:

1. Environment Variable Setup:

   • Add your API key as an environment variable in a .env file named NSW_TRANSPORT_API_KEY.

2. Server Launch Command:

   npx tfnsw-realtime-alerts-mcp-server
   

3. Debugging Tools: Use the MCP Inspector for detailed debugging and analysis of server responses:

   npm run inspector
   

❓ Frequently Asked Questions (FAQ)

Q1: Which API keys are supported by this server?

A1: The TfNSW Realtime Alerts MCP Server supports API keys from the TfNSW Open Data Hub for authentication.

Q2: Can I use this server with other MCP clients besides Claude Desktop and Continue?

A2: Yes, you can integrate this server with Cursor, but its functionality is limited to tools without specific support for resources and prompts.

Q3: What are the performance implications of using multiple transport modes in filtering alerts?

A3: When filtering by specific transport modes, the query will be more targeted but may result in a higher load on the server as it needs to process separate URI requests. For large data sets, consider batch processing filters or implementing caching mechanisms.

Q4: How often do I need to renew my TfNSW API key?

A4: Typically, API keys are valid for one year. Check the TfNSW Open Data Hub for their validity period and renewal procedures.

Q5: Is there any data latency in real-time alerts retrieval?

A5: The server is designed to minimize latency by processing requests as quickly as possible. However, slight delays might occur due to external factors like network latencies or API response times.

👨‍💻 Development & Contribution Guidelines

Contributions are welcome! If you wish to contribute to the development of the TfNSW Realtime Alerts MCP Server:

1. Code Repository: Find the source code in the project repository on GitHub.
2. Issues Tracking: Report issues or suggest features via the issue tracker.
3. Pull Requests: Submit pull requests for improvements and bug fixes.

Follow best practices like maintaining a clean codebase, writing comprehensive tests, and adhering to existing coding styles.

🌐 MCP Ecosystem & Resources

The TfNSW Realtime Alerts MCP Server is part of a broader MCP ecosystem aimed at enhancing the compatibility and functionality of various AI applications. For more information on other MCP servers and resources, visit the MCP GitHub organization.

By integrating this server into your development workflow, you can significantly enhance the capabilities of your AI applications for transportation-related tasks.