io.ausdata/apra-mcp

Describe a dataset's filterable dimensions, returnable measures, units, source, and (for insurance) framework break info. Use this before calling get_data on a new dataset — it tells you the valid filter keys ('institution', 'sector', 'data_item'), the valid enumerated filter values ('cba', 'major_banks'), the measure aliases ('cet1_ratio', 'total_capital'), and the canonical source URL. For insurance datasets, the response includes a `framework` block documenting the Q3-2023 AASB-17 break. Returns: DatasetDetail with id, name, description, period_coverage, list of dimensions, list of measures, source_url, download_url, and optional framework info.

Query a curated APRA dataset and return observations. Examples: # CBA's CET1 ratio over time resp = await get_data( "ADI_KEY_STATS", filters={"institution": "cba"}, measures="cet1_ratio", ) # Major banks' total capital, last 5 quarters resp = await get_data( "ADI_KEY_STATS", filters={"sector": "major_banks"}, measures="total_capital", start_period="2024-01-01", ) # Total industry gross written premium (general insurance) resp = await get_data( "INSURANCE_GENERAL", filters={"data_item": "Gross written premium", "industry_segment": "total_industry"}, ) # AustralianSuper member account counts resp = await get_data( "SUPER_FUND_LEVEL", filters={"fund_name": "australian_super"}, measures=["total_member_accounts", "total_members_benefits"], ) Returns: DataResponse with records (or csv), unit, period bounds, row_count, source URL, the actual download_url used, optional framework info (insurance only), and CC-BY 3.0 AU attribution.

Return the most recent observation per measure for a dataset. Trims to the single latest period per measure across the filtered slice — useful for "what's CBA's current CET1?" style questions without having to think about start_period. Wide-layout entity-level datasets (INSURANCE_GENERAL etc.) are capped at `limit` rows. Examples: # Latest CBA capital ratios resp = await latest("ADI_KEY_STATS", filters={"institution": "cba"})

List every curated dataset ID in this version of apra-mcp. Returns: Sorted list of dataset IDs.

Fuzzy-search the curated APRA dataset catalog. All datasets ship hand-curated in v0.1: per-bank capital ratios, per-bank risk-weighted assets, fund-by-fund superannuation, and post-AASB17 life + general insurance (with separate historical archives for the pre-Q3-2023 reporting framework). Examples: # Find the dataset for bank capital ratios results = await search_datasets("bank capital cet1") # → [{id: 'ADI_KEY_STATS', name: 'ADI Key Statistics — entity-level...', ...}] # Discover what's available on insurance results = await search_datasets("insurance premium") Returns: List of DatasetSummary (id, name, description, update_frequency, is_curated), ranked by relevance.

Return the N rows with the largest (or smallest) value of a measure. The single most common agent workflow: "show me the top 10 X by Y". top_n does the rank server-side and returns only the requested rows. Examples: # Biggest 10 banks by total capital, latest quarter top_n("ADI_KEY_STATS", "total_capital", n=10, filters={"period": "2025-12-31"}) # Most members per super fund (latest) top_n("SUPER_FUND_LEVEL", "total_member_accounts", n=10, filters={"period": "2025-12-31"}) # 5 lowest CET1 ratios in the latest quarter top_n("ADI_KEY_STATS", "cet1_ratio", n=5, direction="bottom", filters={"period": "2025-12-31"}) Returns: DataResponse with at most `n` records, sorted by `measure` in the requested direction. Other fields match get_data.