Install Aurora and Moose CLIs

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

We’ll be using generative MCP tools here, so make sure you add your Anthropic API key in install. If you installed without adding it, you can add it later with aurora config keys anthropic <your-api-key>. If you need to create one, see: https://docs.anthropic.com/en/docs/initial-setup.

Create a new Moose project from the ADS-B template

aurora init <project-name> ads-b

This will create a new Moose project using the ADS-B template to gather ADS-B (aircraft transponder) data that you can use to explore Aurora’s MCP offerings. By default, it will create the project configured for use with Cursor (by creating ~/.cursor/mcp.config), but if you would like to use Claude Desktop, append --mcp claude-desktop.

If you want to create an empty project, and build your own Data Models and ingestion, try aurora init <project-name> typescript-empty or aurora init <project-name> python-empty

Install dependencies and run the dev server

Navigate into the created project directory:

cd <project-name>

Install the dependencies:

npm i

Run the dev server:

moose dev

Set up your client: open Cursor and Enable the MCPs

Then open your code editor (e.g. by cursor .).

Cursor should prompt you to enable the MCP. If it doesn’t, go to cursor > settings > cursor settings > MCP and enable the MCP called “aurora”. Note, the tools will not all work until the dev server is run locally! Note, you might need to refresh the MCP until its status indicator shows 🟢.

Start Ingesting Data

Run the command to start ingesting data with the configured ingest scripts: moose workflow run military_aircraft_tracking

You should start to see hundreds of live datapoints ingesting instantly!

Enrich project with metadata [coming soon]

Since we have a Moose project with sample data and some metadata, we can use this to create more metadata!

If we ask our client “Can you add a description to each Moose primitive in this project?”, the LLM will use the write_metadata tool to add a description to each Moose primitive.

const acPipeline = new IngestPipeline<AircraftTrackingProcessed>(
    "AircraftTrackingProcessed",
    {
      table: true,
      stream: true,
      ingest: false,
      metadata: {
          description: "Pipeline for ingesting raw aircraft data" } // new description field!
      }
    
);

Chat with your data

You can also now just chat with your client about your data! Try asking “What aircraft are listed in the data I have available.”

The client will use read_moose_project, read_clickhouse_tables and maybe read_production_clickhouse to answer your question.

Create new Egress APIs with Aurora MCP tools

If you find a thread that you find interesting enough to want to productionize, try asking the client “can you create an egress API to furnish that data?”

The client will use create_egress_api and test_egress_api to create an egress API primitives in Moose, that will automatically deploy in your local dev environment when you save.