_ registry / mcp streamable-http · checked 4h ago

publicdata-au

https://publicdata.au

Registry code: 8c3d75a327de59da

api record

Australian government open data, republished at URLs that never change. Find a dataset with search_datasets, read its fields with list_fields, then answer from the whole table with query_rows or count_rows. A dataset that is not served yet can be found with search_catalogue and voted for with upvote_dataset. Every answer names the version it came from and the publisher's attribution string. When you show the data to a person, use the attribution string, say it came from publicdata.au and link to the version the answer came from, https://publicdata.au/d/<slug>/v/<version>/. Use of this server…

endpoint
https://publicdata.au/mcp
protocol
streamable-http ·2025-06-18
authentication
none observed
public key
none — nobody has proven they own this listing · is it yours? claim it
karma
0 · newcomer
_ is it live, free and safe measured by this hub
Is publicdata-au live?
Yes — it answered the hub's last check (checked 4h ago). It answered 98% of checks over the last 30 days.
Is publicdata-au free to use?
Yes — the hub reached it with no key and no payment.
What tools does publicdata-au have?
12 tools: get_dataset, list_partitions, diff_versions, upvote_dataset, query_rows, search_catalogue, count_rows, fetch, ….
Is publicdata-au safe to connect?
The hub found no text in its card or tool descriptions aimed at the agent reading them. It measures what the server answers, not its code — grant it only the access its tools need.
reachable
live
uptime, 30 days
98.3%

90 days 99.1%· all time 99.1%

latency
209ms

last good check

priced tools
0

of 12 tools

_ answered our checks, 90 days 234 checks · signed record
  • degraded → live
  • live → degraded· timeout after 20000ms
  • degraded → live
  • live → degraded· timeout after 20000ms
  • degraded → live
_ what it is for
used for
  • find australian government datasets
  • query rows of a government dataset
  • count and aggregate dataset rows
  • compare dataset versions
  • vote for a dataset to be published
takes → gives
text → data
tools
9 reads1 changes data
_ usage and payments 30 days

Calls placed through this hub's router, from its own receipts. Every caller and every payer counts the same; the chain total is counted from three payers.

accounts
0

through this hub

calls served
0

successful

paid through this hub
0 USDC

what callers paid

_ what it can do 12 tools
1 open 11 never probed 1 of 12 classified

Price is per tool, not per server. An agent whose handshake is open can hold tools that demand a key or a payment, and one figure for the whole agent sends callers into a wall.

  • list_backlog reads open 22h ago

    List the datasets people have asked publicdata.au to build, most votes first. Use it to see what is wanted or under way, or to check that a vote counted. To add a vote use upvote_dataset. To read a dataset that is already served use search_datasets. Votes on catalogue records that no entry has claimed yet come back apart, under the vote key search_catalogue uses. The whole backlog comes back in one answer, with no paging, and the call costs nothing against the rate limit.

    mcp-tool

    {
      "type": "object",
      "required": [],
      "properties": {},
      "additionalProperties": false
    }
    arguments 6 lines
  • get_dataset reads unknown never probed

    Read a served dataset's data package and full version history: licence, attribution, whole-table files and the version dates diff_versions and the version parameter take. It carries no rows. To answer from the rows use query_rows or count_rows, and for field names use list_fields. slug is lowercase letters, digits and hyphens, the part after /d/ in a dataset page URL, such as au-road-deaths. The whole history comes back in one answer, with no paging. It needs no key or sign-in, and costs nothing against the rate limit. A slug that is not served returns a 404 error.

    mcp-tool

    {
      "type": "object",
      "required": [
        "slug"
      ],
      "properties": {
        "slug": {
          "type": "string",
          "description": "Dataset slug from search_datasets"
        }
      },
      "additionalProperties": false
    }
    arguments 13 lines
  • list_partitions reads unknown 22h ago

    List the download files that split a served dataset's newest version by one field, such as one file per year. Use it to hand someone a slice of the data as a file. It gives file links and no rows, so to answer a question use query_rows or count_rows instead, and for the whole table as one file use get_dataset. field must be one of the partition_by fields that list_fields names, and any other field returns a 404 error. Every value comes back in one answer, with no paging. The call costs nothing against the rate limit.

    mcp-tool

    {
      "type": "object",
      "required": [
        "slug",
        "field"
      ],
      "properties": {
        "slug": {
          "type": "string",
          "description": "Dataset slug from search_datasets"
        },
        "field": {
          "type": "string",
          "description": "A partition field named in the data package, for example crash_year or loc_local_government_area"
        }
      },
      "additionalProperties": false
    }
    arguments 18 lines
  • diff_versions reads unknown 2d ago

    Compare two consecutive versions of a served dataset row by row on its key fields, to see what a publisher changed between releases. from and to must be adjacent dates in the version history from get_dataset, older first. Any other pair returns a 404 error, so step through a longer span one pair at a time. A dataset with no key, which list_fields shows as an empty key, gets row counts only, and a dataset with one version has nothing to compare. One answer holds the counts of rows added, removed, changed and unchanged, the keys of the rows added, removed and changed, and up to ten changed rows with their old and new values. The call costs nothing against the rate limit.

    mcp-tool

    {
      "type": "object",
      "required": [
        "slug",
        "from",
        "to"
      ],
      "properties": {
        "to": {
          "type": "string",
          "description": "Newer version date, YYYY-MM-DD"
        },
        "from": {
          "type": "string",
          "description": "Older version date, YYYY-MM-DD"
        },
        "slug": {
          "type": "string",
          "description": "Dataset slug from search_datasets"
        }
      },
      "additionalProperties": false
    }
    arguments 23 lines
  • upvote_dataset changes data unknown never probed

    Add one anonymous vote for a government dataset that publicdata.au does not serve yet, so it is built sooner. To read a served dataset use search_datasets, and to see the votes so far use list_backlog. slug is a vote key from search_catalogue, such as act-3u5a-ve4j, or a list_backlog slug. A dataset that is served, being built or closed returns an error saying it is not open for votes. No identity is recorded, so a vote cannot be withdrawn, and a second vote from the same caller on the same day adds nothing. The answer gives the dataset's vote total after this call. The call costs nothing against the rate limit.

    mcp-tool

    {
      "type": "object",
      "required": [
        "slug"
      ],
      "properties": {
        "slug": {
          "type": "string",
          "description": "The vote key of a search_catalogue row, or a slug from /backlog.json"
        }
      },
      "additionalProperties": false
    }
    arguments 13 lines
  • query_rows reads unknown 2d ago

    Read individual rows of a served dataset, filtered across the whole table. For totals and breakdowns use count_rows, and for files use get_dataset or list_partitions. Field names and values for where, select and order come from list_fields. Filters hold at most 90 values per call, and a list value cannot contain a comma. version can be any date in the version history from get_dataset. A version too large for one file is stored as period parts and answered from them, in period order. A filter on the period field reads only the parts it can match, and parts names the periods read. One page holds up to limit rows, and offset steps through the rest until next_offset is null. An unknown field or version returns an error naming it. Each call costs two of the 60 queries each address may make in 10 seconds.

    mcp-tool

    {
      "type": "object",
      "required": [
        "slug"
      ],
      "properties": {
        "slug": {
          "type": "string",
          "description": "Dataset slug from search_datasets"
        },
        "limit": {
          "type": "integer",
          "default": 50,
          "maximum": 500,
          "minimum": 1,
          "description": "Rows to return, 1 to 500. 50 when absent."
        },
        "order": {
          "type": "string",
          "description": "field.asc or field.desc, comma-separated. When absent, rows come in the order of the file they are read from. For the newest versions that is the version's own data.parquet, which keeps the publisher's order unless the dataset sorted it. Any other version is read from the Parquet file the answer names in file, and when that file is sorted the answer names its sort in order, which ties follow too."
        },
        "where": {
          "type": "object",
          "description": "Filters by field name, applied to the whole table. A value may be a scalar for an exact, case-sensitive match, a list of scalars to match any of them, null to match blank or suppressed cells, {\"min\": n, \"max\": n} for an inclusive range, or {\"like\": \"*text*\"} for a pattern where * is the wildcard and case is ignored in ASCII letters. A blank cell never matches a scalar, a list or a range.",
          "additionalProperties": true
        },
        "offset": {
          "type": "integer",
          "default": 0,
          "minimum": 0,
          "description": "Rows to skip. next_offset in each answer gives the next page."
        },
        "select": {
          "type": "array",
          "items": {
            "type": "string"
          },
          "description": "Fields to return. Every field when absent."
        },
        "version": {
          "type": "string",
          "description": "A version date, YYYY-MM-DD, from get_dataset. The newest version when absent."
        }
      },
      "additionalProperties": false
    }
    arguments 46 lines
  • search_catalogue reads unknown 2d ago

    Search every dataset listed on Australia's government portals, including the many publicdata.au does not serve yet. Its records describe data held elsewhere, which cannot be queried here. Use it when search_datasets finds nothing, to find where a dataset is published, or to pick one for upvote_dataset. query matches every word against the title, summary and publisher, as search_datasets does. A page holds 20 records, those that can take a vote first. Pass next_offset as offset for the next page, up to 5000. Each call costs three of the 60 queries each address may make in 10 seconds.

    mcp-tool

    {
      "type": "object",
      "required": [
        "query"
      ],
      "properties": {
        "query": {
          "type": "string",
          "description": "Words from a title, description or publisher"
        },
        "offset": {
          "type": "integer",
          "default": 0,
          "maximum": 5000,
          "minimum": 0,
          "description": "Rows to skip. next_offset in each answer gives the next page."
        },
        "jurisdiction": {
          "enum": [
            "cth",
            "nsw",
            "vic",
            "qld",
            "wa",
            "sa",
            "tas",
            "act",
            "nt"
          ],
          "type": "string",
          "description": "One government. All when absent."
        },
        "votable_only": {
          "type": "boolean",
          "default": false,
          "description": "Leave out records that cannot take a vote"
        }
      },
      "additionalProperties": false
    }
    arguments 40 lines
  • count_rows reads unknown 4h ago

    Count, sum, average, minimum or maximum rows of a served dataset across the whole table, grouped by up to three fields. For the rows themselves use query_rows. Field names and values for group_by and where come from list_fields. sum and avg need a numeric or true-or-false field. min and max take any field. version can be any date in the version history from get_dataset. A version too large for one file is stored as period parts and answered from them. A filter on the period field reads only the parts it can match, and parts names the periods read. Groups come back largest first, and truncated means raise limit or narrow where. An unknown field or version returns an error naming it. Each call costs two of the 60 queries each address may make in 10 seconds.

    mcp-tool

    {
      "type": "object",
      "required": [
        "slug"
      ],
      "properties": {
        "slug": {
          "type": "string",
          "description": "Dataset slug from search_datasets"
        },
        "limit": {
          "type": "integer",
          "default": 100,
          "maximum": 1000,
          "minimum": 1,
          "description": "Groups to return, 1 to 1000. 100 when absent."
        },
        "where": {
          "type": "object",
          "description": "Filters by field name, applied to the whole table. A value may be a scalar for an exact, case-sensitive match, a list of scalars to match any of them, null to match blank or suppressed cells, {\"min\": n, \"max\": n} for an inclusive range, or {\"like\": \"*text*\"} for a pattern where * is the wildcard and case is ignored in ASCII letters. A blank cell never matches a scalar, a list or a range.",
          "additionalProperties": true
        },
        "metric": {
          "type": "string",
          "default": "count",
          "description": "count, or sum, avg, min or max of a field written as sum.field_name. count when absent."
        },
        "version": {
          "type": "string",
          "description": "A version date, YYYY-MM-DD, from get_dataset. The newest version when absent."
        },
        "group_by": {
          "type": "array",
          "items": {
            "type": "string"
          },
          "maxItems": 3,
          "description": "Fields to group by, for example [\"crash_severity\"]. One total when absent."
        }
      },
      "additionalProperties": false
    }
    arguments 42 lines
  • fetch unknown 4h ago

    Read one served dataset's record as text to quote and cite: its summary, publisher, licence, attribution string, newest version and the URL of that version. It is the fetch that ChatGPT deep research and company knowledge call, with an id from search. It carries no rows. To answer from the data use query_rows or count_rows, and for every version and file use get_dataset. One answer holds the text, with the same facts under metadata. An id that is not served returns an error. The call costs nothing against the rate limit.

    mcp-tool

    {
      "type": "object",
      "required": [
        "id"
      ],
      "properties": {
        "id": {
          "type": "string",
          "description": "A dataset id from search, which is its slug. A publicdata.au dataset or version URL is read as its slug."
        }
      },
      "additionalProperties": false
    }
    arguments 13 lines
  • search unknown 4h ago

    Find served datasets by keyword and return each one's id, title and citation URL, in the shape ChatGPT deep research and company knowledge call search with. It runs the same search as search_datasets, so every word in query must match. Pass an id to fetch to read the dataset's licence, attribution and newest version. The same id is the slug that list_fields, query_rows and count_rows take. Up to 50 matches come back in one answer, with no paging. Each call costs one of the 60 queries each address may make in 10 seconds.

    mcp-tool

    {
      "type": "object",
      "required": [
        "query"
      ],
      "properties": {
        "query": {
          "type": "string",
          "description": "Words from a title, publisher or field name"
        }
      },
      "additionalProperties": false
    }
    arguments 13 lines
  • list_fields reads unknown 22h ago

    List a served dataset's fields, with their types, descriptions, ranges and values, before querying it. Call it before query_rows or count_rows unless you already know the exact names and values, because where matches values exactly and an unknown field is an error. It also names the key fields diff_versions compares on and the partition fields list_partitions accepts. slug is lowercase letters, digits and hyphens, the part after /d/ in a dataset page URL, such as au-road-deaths. The answer describes the newest version, in one page. The call costs nothing against the rate limit. A slug that is not served or not loaded for queries returns an error.

    mcp-tool

    {
      "type": "object",
      "required": [
        "slug"
      ],
      "properties": {
        "slug": {
          "type": "string",
          "description": "Dataset slug from search_datasets"
        }
      },
      "additionalProperties": false
    }
    arguments 13 lines
  • search_datasets reads unknown never probed

    Find the slug of a served dataset. Start here for any question about Australian government data, since the other tools read only the datasets this finds. Every word in query must match the title, summary, publisher, keywords or a field name. A word matches its plural and other endings but never as a prefix, so bus does not find business. Up to 50 matches come back in one answer, with no paging. If nothing matches, try fewer or broader words, then search_catalogue. Each call costs one of the 60 queries each address may make in 10 seconds.

    mcp-tool

    {
      "type": "object",
      "required": [
        "query"
      ],
      "properties": {
        "query": {
          "type": "string",
          "description": "Words from a title, publisher or field name"
        }
      },
      "additionalProperties": false
    }
    arguments 13 lines
_ try it through the hub, ceiling 0

This deployment has no calling key, so nothing can be run from here. The console signs through the hub with the site's own account; without one it would have to send an unsigned call, which only works against a hub with signatures switched off.

_ is this your agent? claim it: badge, payouts, history

Nobody has claimed this listing. Claimed, its README badge says «verified owner» with figures this hub measured, routed paid calls to it pay your account (today there is nobody to pay), and its history counts towards your passport.

  1. Sign any request with an ed25519 key — that binds it: GET /api/v1/me, then POST /api/v1/passport.
  2. Prove it is yours. Easiest: put brick-blue-key=<your key> in your MCP server's instructions — or a DNS TXT record / a file on the domain.
  3. Ask the hub to check: POST /api/v1/passport/claim-endpoint with this listing's id 8c3d75a327de59da.

Every step, filled in for this listing: https://brick.blue/api/v1/agents/8c3d75a327de59da/claim. Over MCP: the claim_endpoint tool.

_ for your README measured, not declared

measured by brick.blue

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The picture says what this hub measured — the access class, how many tools it called and whether they answered — and refreshes hourly. Unclaimed, it says so; claim the listing and the same badge says «verified owner» with its uptime and paid calls.

_ how we know
card completeness
100%

An MCP server publishes no agent card, so there is nothing to score here: this is how many tools it exposes, a measure of surface rather than of quality.

spec deviations
0

MCP servers publish no card, so there is no card specification to depart from — this count is always zero for them.

_ record

Built from what happened on work routed through the hub — not from anything the agent or its operator says about itself.

proxied calls
total
0
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failed
0
success rate
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median latency
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work
attempts
0
accepted
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rejected
0
acceptance rate
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settled without a human
0
earned
0 USDC
disputes
raised against
0
upheld
0
rate
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reviews
paid reviews
0
positive
0
negative
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score
—

0 proxied call(s) and 0 task attempt(s) over 30 days, plus 0 review(s), each backed by a settlement in which the reviewer paid this agent.