From data to app with Lovable

Using the Nekt MCP tools, create the tables my app will read.

I am building an app with these screens: [describe each screen, for example:
a KPI header, a monthly revenue chart, and a searchable customer list].

For each screen:
- Create a scheduled Query in Nekt that writes a clean table to the trusted layer.
- Name each table app_<screen>, for example app_kpis, app_monthly_revenue,
  app_customers.
- Shape each table so it matches exactly what the screen shows, one row per data
  point, so the app does not have to transform anything.
- Give every table a stable, unique identifier column I can use as a primary key.
- Schedule it to refresh daily.

When done, list the tables you created with their columns and types.

You have access to my Nekt MCP server.

1. List the tables available in Nekt and preview a few rows of each app_* table.
2. Build a dashboard with one section per table:
   - app_kpis as a KPI header row
   - app_monthly_revenue as a line chart
   - app_customers as a searchable, paginated table
3. Use the real column names and types from Nekt. Do not invent fields.
4. For now, seed the UI with the sample rows you previewed so I can review the
   layout. I will wire up live data next.

Add live data from Nekt to this app using the Nekt Data API.

Create a Supabase Edge Function called nekt-data that:
- Reads my API key from the NEKT_API_KEY secret. Never expose it to the browser.
- Calls POST https://api.nekt.ai/api/v1/sql-query/
    - Header: x-api-key: <NEKT_API_KEY>, Content-Type: application/json
    - Body: {"sql": "<a SELECT against one app_* table>", "mode": "csv"}
- Reads presigned_urls from the response, downloads the CSV from the first URL,
  and parses it into rows.
- Runs one query per table (app_kpis, app_monthly_revenue, app_customers) in
  parallel and returns all datasets as JSON keyed by section.
- Only runs SQL from a fixed list defined inside the function. Never accept SQL
  from the client.
- Caches each result for 1 hour, since the tables refresh daily.

Then update the app to call this function on load and render each dataset into
its matching section, with loading and error states.

Nekt loads tables into my Supabase database on a schedule. Secure them:

1. Enable row level security on every table in the nekt schema.
2. Add a policy that allows authenticated users to SELECT, and nothing else.
   No INSERT, UPDATE, or DELETE from the client, since Nekt owns this data and
   any writes will be overwritten on the next sync.
3. If a table should only be visible to certain users, ask me which column
   identifies the owner and scope the policy to it.

Build the app against the Nekt-managed tables in my Supabase database:

- app_kpis renders as a KPI header row.
- app_monthly_revenue renders as a line chart.
- app_customers renders as a table with server-side search, sorting, and
  pagination, querying Supabase directly rather than loading everything at once.

Treat these tables as read-only. Never write to them from the app.