Templates

Adsb

Aircraft Transponder (ADS-B) Template

This template allows you to ingest and analyze aircraft transponder data (ADS-B) from military aircraft. It demonstrates how to build a data pipeline that collects aircraft tracking information, processes it in real-time, and stores it in ClickHouse for analysis.

Getting Started

Prerequisites

Before getting started, make sure you have the following installed:

Requirements
- NodeJS
- Docker Desktop

Install Moose and Aurora

To get started, install Moose (open source developer platform for data engineering) and Aurora (AI data engineering product).

terminal
bash -i <(curl -fsSL https://fiveonefour.com/install.sh) moose,aurora

Anthropic API Key

This installation will ask for your Anthropic API key if you want to use the AI features. If you don’t have one, you can follow the setup guide at Anthropic’s website.

Create a new project using the ADS-B template

terminal
aurora init aircraft ads-b --mcp claude-desktop

Set up the project

Navigate to the project directory and install dependencies:

terminal
cd aircraft
npm install

Start the Docker services

Make sure Docker Desktop is running, then start the Moose development server:

terminal
moose dev

This will start all necessary local infrastructure including ClickHouse, Redpanda, Temporal, and the Rust ingest servers.

Run the data ingestion workflow

Open a new terminal window and navigate to your project directory, then run:

terminal
moose workflow run military_aircraft_tracking

This workflow will retrieve data from the adsb.lol military aircraft tracking API, process it according to the data model, and ingest it into ClickHouse.

Explore the Data

The template allows you to explore the ingested aircraft data using AI tools like Claude Desktop or Cursor.

Explore with Claude Desktop

Claude Desktop can help you analyze the data through natural language queries.

Example Questions for Claude

Try asking Claude exploratory questions like:

  • “Tell me about the data in my ClickHouse tables”
  • “Tell me about the flow of data in Moose project”
  • “Create a pie chart of the types of aircraft in the air right now”
  • “Create a visualization of aircraft type against altitude”

Productionize Your Results with Cursor

For a code-forward workflow, Cursor provides a great environment to productionize your queries.

Configure Cursor with Aurora MCP

terminal
cd path/to/your/project
cursor .

Then run the Aurora command to configure the MCP for Cursor:

terminal
aurora setup --mcp cursor-project

This will create a /.cursor/mcp.json file with Aurora’s MCP configuration.

Enable the MCP in Cursor by going to: cursor > settings > cursor settings > MCP and clicking enable and refresh.

Example Question for Cursor

Try asking Cursor to help you productionize your analysis: “Could you create an egress API that, for a given aircraft type input, returns the altitude, and longitude of each instance of that aircraft?”

Project Structure

The template implements a data pipeline that:

  1. Fetches military aircraft data from the adsb.lol API
  2. Processes and normalizes the data (handling special cases like the “ground” altitude)
  3. Enriches the data with additional metrics like Z-order coordinates
  4. Stores the data in ClickHouse for analysis
aircraft/
├── app/
│   ├── datamodels/        # Data models for aircraft tracking
│   ├── functions/         # Processing functions for aircraft data
│   └── scripts/           # Workflow scripts for data ingestion
└── README.md              # Project documentation

Next Steps

Once you have the data flowing, you can:

  1. Build custom visualizations of aircraft movement
  2. Create alerting systems for specific aircraft types or behaviors
  3. Analyze flight patterns and trends over time
  4. Create APIs to surface insights from your data

Feel free to modify the data models, processing functions, or create new APIs to suit your specific needs!

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