MCP server for the Australian Bureau of Statistics Data API. Hides SDMX behind plain-English tools, with curated mappings for Labour Force, CPI, ERP, Building Approvals, and Lending Indicators.
Project description
abs-mcp
An MCP server that wraps the Australian Bureau of Statistics Data API and hides SDMX behind plain-English tools. Ask Claude "What's the unemployment rate in NSW?" and get a real answer with a source link, instead of a wall of SDMX codes.
Five tools, hand-curated mappings for Labour Force, CPI, Estimated Resident Population, Building Approvals, and Lending Indicators.
Install
# After publish:
uvx abs-mcp
# Local dev install:
uv pip install -e .
Claude Desktop
Add to ~/Library/Application Support/Claude/claude_desktop_config.json:
{
"mcpServers": {
"abs": {
"command": "uvx",
"args": ["abs-mcp"]
}
}
}
For a local checkout (before PyPI publish):
{
"mcpServers": {
"abs": {
"command": "uv",
"args": ["run", "--directory", "/absolute/path/to/abs-mcp", "abs-mcp"]
}
}
}
Restart Claude Desktop. The abs server appears in the tools panel with five tools.
Cursor
Add to ~/.cursor/mcp.json (or workspace .cursor/mcp.json):
{
"mcpServers": {
"abs": {
"command": "uvx",
"args": ["abs-mcp"]
}
}
}
Tools
| Tool | What it does |
|---|---|
search_datasets(query, limit=10) |
Fuzzy-search ABS dataflow names. Returns the top matches. |
describe_dataset(dataset_id) |
Plain-English description of a dataflow's dimensions and values. |
get_data(dataset_id, filters, start_period, end_period, format) |
Query a dataflow with filters. Returns clean records (default), grouped series, or CSV. |
latest(dataset_id, filters) |
Just the most recent observation(s) — wraps get_data with lastNObservations=1. |
list_curated() |
The five dataflow IDs that have hand-curated plain-English support. |
Curated dataflows
For these five, filters accepts plain-English values (e.g. "region": "nsw" instead of "REGION": "1"):
- LF — Labour Force, monthly: employment, unemployment, participation by state/sex
- CPI — Consumer Price Index, quarterly inflation by capital city and category
- ABS_ANNUAL_ERP_ASGS2021 — Estimated Resident Population, annual by state and sub-state geography
- BA_GCCSA — Building Approvals, monthly by state/capital region and building type
- LEND_HOUSING — Lending Indicators, monthly housing finance commitments by purpose, lender, and state
Any other ABS dataflow still works — pass raw SDMX dimension IDs and codes.
Worked examples
"What's the current unemployment rate in NSW?"
Claude calls:
latest(dataset_id="LF", filters={"region": "nsw", "measure": "unemployment_rate"})
Returns:
{
"dataset_id": "LF",
"dataset_name": "Labour Force",
"query": {"region": "nsw", "measure": "unemployment_rate"},
"period": {"start": "2026-03", "end": "2026-03"},
"records": [
{
"period": "2026-03",
"value": 4.2,
"dimensions": {"measure": "Unemployment rate", "region": "New South Wales", "sex": "Persons"}
}
],
"source": "Australian Bureau of Statistics",
"abs_url": "https://www.abs.gov.au/statistics/labour/employment-and-unemployment/labour-force-australia"
}
"Show me NSW housing approvals over the last two years"
get_data(dataset_id="BA_GCCSA", filters={"region": "nsw", "measure": "dwelling_units"}, start_period="2024")
"Compare quarterly CPI in Sydney vs Melbourne"
get_data(dataset_id="CPI", filters={"region": ["sydney", "melbourne"], "measure": "change_year"}, start_period="2023")
Period formats
ABS uses different period formats per dataflow:
- Monthly (LF, BA_GCCSA, LEND_HOUSING):
"2026-03" - Quarterly (CPI):
"2024-Q1" - Annual (ABS_ANNUAL_ERP_ASGS2021):
"2024"
Pass start_period / end_period in the matching format.
Development
git clone https://github.com/Bigred97/abs-mcp.git
cd abs-mcp
uv sync --extra dev
uv pip install -e .
# Unit tests (no network)
uv run pytest
# Live integration tests (hits real ABS API)
uv run pytest -m live
The SQLite cache lives at ~/.abs-mcp/cache.db. Catalogue refreshes every 24h, codelists every 7 days, data responses every hour, latest 15 minutes. Delete the file to force a refresh.
How it differs from existing ABS MCP servers
The one existing community option (seansoreilly/abs) exposes a single query_dataset tool that passes raw SDMX through. This package offers semantic tools and curated mappings for the highest-value dataflows so an LLM can answer real questions without you needing to know what M13.3.1599.20.1.M means.
License
MIT — Harry Vass, 2026.
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