Public toilets, ACT

As it appears in data.json.

GET https://publicdata.au/d/act-public-toilets/latest/data.json
{
  "asset_type": "PUBLIC TOILET",
  "asset_sub_type": "MANUAL STYLE ABLUTION BLOCK",
  "asset_id": "TOLT18",
  "asset_name": "HAIG PARK MANUAL STYLE ABLUTION BLOCK",
  "location": "HAIG PARK",
  "operational_state": "ACTIVE",
  "disabled_cubicle": "DISABLED ACCESS",
  "male_cubicle_number": 1,
  "female_cubicle_number": 2,
  "unisex_cubicle_number": 0,
  "disabled_cubicle_number": 0,
  "urinal_number": 0,
  "total_no_of_cubicles": 3,
  "sink_number": 0,
  "toilet_access": "AEST 7AM TO 8PM, AEDT 7AM TO 10PM",
  "water_supply": null,
  "toilet_system": null,
  "suburb": "BRADDON",
  "address": "BRADDON,ACT,2612,AUSTRALIA",
  "ownership": "PLACE MANAGEMENT",
  "maintained_by": "PM - INNER NORTH OPERATIONS",
  "last_edited_date": "2024-07-11",
  "globalid": "291c67ba-a2f3-487c-b923-c1d631a52263",
  "longitude": 149.131804599375,
  "latitude": -35.2701375493569
}Copy

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https://publicdata.au/mcp is a remote MCP server over Streamable HTTP with the same tools, defined in the same place, so a tool added to the pages is added here too. It needs no key and no account. Its row tools and the query API answer every version through one query path, so a tool's answer and the query URL it cites give the same rows. A query that would read too much of a file is refused with DuckDB SQL that answers it from the file. It also has search and fetch, the two tools ChatGPT's deep research and company knowledge call by name, which run search_datasets and read a dataset's record in the shapes those features expect. The row tools are held to the query API's limit of 60 queries in 10 seconds from one address, and each call is two queries because it also counts the matching rows. Add it to Claude Code with claude mcp add --transport http publicdata https://publicdata.au/mcp, add the URL in Claude as a custom connector, or give it to any client that connects to remote MCP servers. Each dataset with a table is also a resource at https://publicdata.au/d/<slug>/fields.json, which lists its fields with their types, the publisher's descriptions, their ranges and the values they hold, so an agent can read a dataset's shape before it writes a query.