Fuzzy-search the curated ASIC dataset catalogue.

The curated set of hand-curated ASIC registers covers Financial Advisers, AFS Licensees, AFS Authorised Representatives, Credit Licensees, Credit Representatives, Banned and Disqualified Persons, Banned and Disqualified Organisations, Registered Liquidators, Registered Company Auditors, SMSF Auditors, Companies, Business Names, and Short Positions. Call list_curated() to get the live list rather than assuming a fixed count — the registry grows over time.

Examples: # Find the financial advisers register results = await search_datasets("financial adviser") # → [{id: 'ASIC_FINANCIAL_ADVISERS', name: 'Financial Advisers Register', ...}]

# Discover what's available on enforcement-related lists
results = await search_datasets("banned")

Returns: List of DatasetSummary (id, name, description, update_frequency, is_curated), ranked by relevance.

Describe a dataset's filterable dimensions, returnable measures, and source.

Use this before calling get_data on a new dataset — it tells you the valid filter keys ('current_status', 'state', 'business_name'), the valid filter values ('current', 'ceased', 'nsw', 'vic'), and the source URL.

Returns: DatasetDetail with id, name, description, period_coverage, list of dimensions, list of measures, source_url, and download_url.

Query a curated ASIC register dataset and return matching rows.

Examples: # All currently registered financial advisers in NSW resp = await get_data( "ASIC_FINANCIAL_ADVISERS", filters={"current_status": "current", "state": "nsw"}, )

# AFS licensees whose legal name contains "Macquarie"
resp = await get_data(
    "ASIC_AFS_LICENSEE",
    filters={"licensee_name": "Macquarie"},
)

# Persons banned or disqualified after 2024
resp = await get_data(
    "ASIC_BANNED_PERSONS",
    start_period="2024-01-01",
)

# Full authorisation text for one AFS licensee
resp = await get_data(
    "ASIC_AFS_LICENSEE",
    filters={"licensee_name": "Macquarie Bank Limited"},
    include_full_authorisation=True,
)

Returns: DataResponse with records (or csv), unit, period bounds, row_count, source URL, and CC-BY 3.0 AU attribution.

Return the most recent observation(s) per measure for a dataset.

For register data, "latest" is the current weekly/monthly snapshot capped at limit rows (default 50). For time-bounded fields (date_banned, date_ceased), latest returns the most recent matching record per entity.

Pass filters to drill into one entity (no truncation hits) or raise limit to request more rows.

Examples: # Current registered status for one adviser (precise filter, no truncation) resp = await latest( "ASIC_FINANCIAL_ADVISERS", filters={"adviser_number": "1234567"}, )

# First 50 most-recent banned persons (truncated; full count in resp.truncated_at)
resp = await latest("ASIC_BANNED_PERSONS")

# Get 500 rows in one go (still capped, but bigger window)
resp = await latest("ASIC_AFS_LICENSEE", limit=500)

# Full authorisation text for one AFS licensee
resp = await latest(
    "ASIC_AFS_LICENSEE",
    filters={"licensee_name": "Macquarie Bank Limited"},
    include_full_authorisation=True,
)

List every curated dataset ID in this version of asic-mcp.

These are the datasets where get_data accepts plain-English filter keys and returns aliased, well-typed columns. Each ID is documented via describe_dataset.

Returns: Sorted list of dataset IDs.