io.ausdata/rba-mcp

Describe an RBA F-table's series, units, and frequency. For curated F-tables (F1.1, F4, F6, F11, F11.1), returns plain-English series keys (like 'cash_rate_target', 'aud_usd') with descriptions and units. For other F-tables, fetches the CSV and returns the raw RBA series IDs from the header along with start dates. Examples: # Curated table — plain-English keys detail = await describe_table("F1.1") # detail.series[0]: key='cash_rate_target', series_id='FIRMMCRT', # unit='Per cent per annum', frequency='Daily' # Curated FX table detail = await describe_table("F11.1") # detail.series has 'aud_usd', 'aud_eur', 'aud_jpy', 'aud_cny', etc. When to use: - Before calling get_data on a new table — to discover valid series keys - To get the canonical RBA source URL for citation - To distinguish curated (plain-English) tables from raw F-tables Returns: TableDetail with id, name, description, is_curated flag, frequency, list of SeriesDetail (key, series_id, description, unit), and rba_url.

Query an RBA F-table and return observations. Curated tables accept plain-English series keys that map to canonical RBA series IDs server-side. Omit `series` to get the table's headline series (e.g. F1.1 → cash rate target, F11/F11.1 → AUD/USD, F6 → owner- occupier outstanding variable rate). Pass an explicit list for a multi- series query. Examples: # Cash rate target since 2020 (portfolio-standard name) resp = await get_data("F1.1", series="cash_rate_target", start_period="2020") # → resp.records[0]: period='2020-01-01', value=0.25, series='cash_rate_target' # Headline default — no series arg returns the table's canonical series resp = await get_data("F11.1", start_period="2024-01-01", end_period="2024-12-31") # → resp.records: AUD/USD daily (the headline) for the period # Multiple FX rates — pass an explicit list resp = await get_data( "F11.1", series=["aud_usd", "aud_eur", "aud_jpy"], start_period="2024-01-01", end_period="2024-12-31", ) # Mortgage rates as CSV resp = await get_data("F6", format="csv", start_period="2023") # → resp.csv = "date,series,value 2023-01-01,..." # Raw (non-curated) F-table — pass raw RBA series IDs resp = await get_data("F1", series=["FIRMMCRTD", "FIRMMBAB30"]) # Legacy alias still works (start_date / end_date) resp = await get_data("F11", series="aud_usd", start_date="2024") Parameter notes: - Prefer `start_period` / `end_period` (portfolio-standard names; 7 of 9 sister MCPs use them). - `start_date` / `end_date` are retained as legacy aliases. Supplying both `start_period` and `start_date` (or `end_period` and `end_date`) raises ValueError — pick one per pair. When to use: - You want a time series of an RBA indicator (use latest() for current-only) - You want…

Return the most recent observation for each series in an RBA F-table. Wraps get_data with last_n=1 (and a shorter cache TTL). Use this for "what's the current X?" questions — it's a cheap, fast call. Examples: # Current cash rate target (explicit) resp = await latest("F1.1", series="cash_rate_target") # → resp.records[0]: period='2026-05-06', value=3.85, unit='Per cent per annum' # Headline default — no series arg returns the table's canonical series. # F1.1 → cash rate target; F11/F11.1 → AUD/USD; F6 → average mortgage rate. resp = await latest("F1.1") # → resp.records[0]: cash_rate_target only (the table's headline) # Snapshot multiple FX rates in one call resp = await latest("F11.1", series=["aud_usd", "aud_eur", "aud_jpy"]) # Latest owner-occupier variable mortgage rate resp = await latest("F6", series="owner_occupier_variable_existing") When to use: - You want the current value of an RBA indicator - You want a current-snapshot of multiple series in one call (pass an explicit list — e.g. all FX rates) - You want sub-50ms warm-cache latency for chat integration Returns: DataResponse with one most-recent observation per requested series.

List every RBA table ID with hand-curated plain-English support. These are the tables where get_data and latest accept plain-English series keys (like 'cash_rate_target', 'aud_usd'). Other tables are still queryable via raw RBA series IDs. The curated set currently spans F-tables (Interest Rates, Money Market Operations, Housing Lending Rates, Exchange Rates, etc.) plus D/C/G/E tables (credit growth, business finance, national accounts). Call this tool to get the live list rather than assuming a fixed count — the registry grows over time (e.g. F1 was added in 0.8.5). Example: ids = list_curated() # → ['C1', 'D1', 'D2', 'E2', 'F1', 'F1.1', 'F11', 'F11.1', # 'F2', 'F2.1', 'F4', 'F5', 'F6', 'F7', 'F8', 'G3'] When to use: - You want to know which tables have plain-English support - You're building a UI / agent that needs the supported set up front - You want to plan which tables to call without inspecting each Returns: Sorted list of curated table IDs. Do not hardcode the count in calling code — query this tool live, since the registry grows.

Upcoming RBA publication schedule (data + statements + events). Scrapes https://www.rba.gov.au/schedules-events/ and merges the two schedule tables into a single chronological feed. Each entry reports `release_at` (Sydney local with UTC offset), `title`, `event_type`, `dataset_id` (curated F-table key when the release refreshes one, else null), `publication_id`, and `source_url`. Event types: - `data_release` — regular statistical publication (Financial Aggregates, Retail Payments, Index of Commodity Prices, etc.) - `statement` — narrative release (Statement on Monetary Policy, Minutes of Monetary Policy Meeting, Financial Stability Review, Bulletin, Chart Pack) - `policy_decision` — cash-rate decisions are NOT exposed here; they appear on a separate RBA page. The Statement on Monetary Policy and Minutes that follow ~24h and ~2 weeks later DO appear, tagged as `statement`. Returns the same envelope shape as `abs-mcp.release_calendar` so a gateway poller can dispatch both feeds through the same code path. Cached at 24h TTL with stale-fallback on 5xx (per portfolio graceful-degradation policy). The gateway should poll on its own schedule rather than hitting the live HTML. Examples: cal = await release_calendar(7) for r in cal.releases: print(r.release_at, r.event_type, r.title, r.publication_id) cal = await release_calendar(60) statements = [r for r in cal.releases if r.event_type == "statement"]

Fuzzy-search RBA F-tables by name and topic. Use this when you don't know the exact table ID. The 5 curated F-tables (F1.1, F4, F6, F11, F11.1) cover the most-asked indicators: cash rate, money-market rates, household lending rates, FX rates. Examples: # Find the F-table that publishes the cash rate results = await search_tables("cash rate") # → [{id: 'F1.1', name: 'Interest Rates and Yields - Money Market', ...}] # Discover what's available on FX results = await search_tables("aud usd", limit=5) # → top 5 FX-related tables, curated F11/F11.1 first When to use: - You have a natural-language question and need to identify the table - You want to discover what RBA publishes on a topic - You're enumerating the F-table catalog programmatically Returns: List of TableSummary (id, name, frequency, description), ranked by relevance. Curated tables surface above the rest.