The Reserve Bank of Australia sets the cash rate target at its monthly board meetings. If your application needs the current cash rate --- for a mortgage calculator, a real-rate display, an AI agent that answers macro questions, or a dashboard --- here is the cleanest way to get it.

The 30-second answer

curl -H "Authorization: Bearer ak_YOUR_KEY" \
  https://api.ausdata.io/v1/data/rba/F1?series=cash_rate_target&limit=1

Returns:

{
  "data": [{
    "period": "2026-05-06",
    "value": 4.10,
    "dimensions": {"series": "cash_rate_target"},
    "unit": "Percent"
  }],
  "meta": {
    "endpoint": "/v1/data/rba/F1",
    "sources": [{
      "name": "Reserve Bank of Australia",
      "url": "https://www.rba.gov.au/statistics/tables/",
      "attribution": "Based on Reserve Bank of Australia data, licensed under CC-BY 4.0."
    }],
    "retrieved_at": "2026-05-27T01:00:00Z",
    "stale": false
  }
}

The value field is the current cash rate in percent. The period field is the date the RBA announced it.

Get a key first

curl -X POST https://api.ausdata.io/v1/register \
  -H "Content-Type: application/json" \
  -d '{"email":"you@example.com"}'

Returns an api_key field starting with ak_. No card, no email verification, no setup. Free tier is 500 calls per month.

Python version

import httpx

KEY = "ak_YOUR_KEY"
response = httpx.get(
    "https://api.ausdata.io/v1/data/rba/F1",
    params={"series": "cash_rate_target", "limit": 1},
    headers={"Authorization": f"Bearer {KEY}"},
)
data = response.json()
cash_rate = data["data"][0]["value"]
period = data["data"][0]["period"]
print(f"Cash rate: {cash_rate}% (as of {period})")

JavaScript / TypeScript version

const key = "ak_YOUR_KEY";
const response = await fetch(
  "https://api.ausdata.io/v1/data/rba/F1?series=cash_rate_target&limit=1",
  { headers: { Authorization: `Bearer ${key}` } }
);
const data = await response.json();
const cashRate = data.data[0].value;
const period = data.data[0].period;
console.log(`Cash rate: ${cashRate}% (as of ${period})`);

MCP version (for AI agents)

If you are building an AI agent using Claude, Cursor, or Windsurf, install the RBA MCP server:

npx ausdata-mcp

Then your agent calls get_data(dataset_id="F1", series="cash_rate_target", limit=1) as a tool, and the response is the same JSON. The model has no need to memorise the cash rate --- it fetches it live.

Why this matters for AI applications

Most large language models have a training cutoff at least 6-18 months before deployment. The RBA changes the cash rate several times per year. Any AI agent that quotes the cash rate from training data will be wrong sooner rather than later. The MCP-server path above keeps your agent grounded on live data.

How the cash rate gets to ausdata.io

The RBA publishes statistical tables at rba.gov.au/statistics/tables/. Table F1 is the daily cash rate. The format is a CSV with row 6 holding units, row 11 holding the series ID, and the data below. Our RBA sister MCP downloads this CSV every 15 minutes, parses it, caches it, and exposes it as JSON via the API.

You can verify any value we return against the RBA published CSV. We do not modify, smooth, or interpolate.

Common gotchas

  1. F1 vs F1.1. F1 is the daily cash rate (every business day). F1.1 is the monthly average. Most consumer-facing apps want F1.
  2. Cash rate target vs interbank cash rate. F1 has both. Use series=cash_rate_target for the official policy rate.
  3. Latest vs historical. With limit=1 you get the latest. To get history, add start_period and end_period like ?start_period=2020-01-01&end_period=2026-05-31.
  4. Date format. The RBA uses ISO dates (YYYY-MM-DD).

Related endpoints

  • /v1/real-rate-regime --- cash rate minus trimmed-mean CPI, with regime classification
  • /v1/data/rba/F4 --- retail deposit rates
  • /v1/data/rba/F6 --- housing lending rates
  • /v1/data/rba/F7 --- business lending rates
  • /v1/economic-dashboard --- cash rate plus 4 other macro indicators in one call

CC-BY licence

RBA data is published under Creative Commons Attribution 4.0. You can use the response in commercial products, articles, and dashboards. Each response includes the full attribution string ready for you to display.

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