ABS Data (observed)

io.github.SamJB123/abs-dataVersion 0.1.0

Australian Bureau of Statistics data: 1,227 tables, offering only options confirmed to serve data

Status

Responds497 msNov 14, 2026, 14:41 UTCAnswered our handshake without sign-in.

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Last checked: Nov 14, 2026, 14:41 UTC
Latency: 497 ms
Remotes responding: 1 of 1
Sign-in: No sign-in
Hosting: Hosted outside the EU (detected)
Registry data as of: Nov 14, 2026, 21:12 UTC

Data from the official MCP Registry, checked by run.zero. How we check

Connect

Streamable HTTP

https://abs-data-front-door.aicolab.workers.dev/mcpResponds497 msNov 14, 2026, 14:41 UTC

No sign-in

Claude Code

claude mcp add --transport http abs-data https://abs-data-front-door.aicolab.workers.dev/mcp

Claude Desktop and claude.ai

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Settings > Connectors > Add custom connector
Name: abs-data
Remote MCP server URL: https://abs-data-front-door.aicolab.workers.dev/mcp

Cursor

{
  "mcpServers": {
    "abs-data": {
      "url": "https://abs-data-front-door.aicolab.workers.dev/mcp"
    }
  }
}

VS Code

code --add-mcp '{"name":"abs-data","type":"http","url":"https://abs-data-front-door.aicolab.workers.dev/mcp"}'

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Tools

8 tools

Tools of ABS Data (observed)
	Description		Read-only	Idempotent	Open world
`describe_table`A table's dimensions in key order, its coverage dates, and its options. Dimensions with up to 64 options list them inline with labels; larger ones (geography, occupations) say how many and are searchable with search_options.	A table's dimensions in key order, its coverage dates, and its options. Dimensions with up to 64 options list them inline with labels; larger ones (geography, occupations) say how many and are searchable with search_options.	No	Yes	Yes	No
`execute`Run JavaScript in an isolated sandbox whose only capability is `abs`, a client with the same four verbs as this server (searchTables, describeTable, searchOptions, getData) and the same guarantees: every selection is verified against ABS before fetching. Use it for multi-series or multi-table analysis — fetch several series, compute growth rates, rank capitals, join tables — and `return` only the computed result, so large payloads never reach the conversation. No network beyond `abs`. Budgets: 10s CPU, 50 calls, 25s wall clock, 200KB result. Your code runs inside an async function; use `await`; console.log is captured. // The `abs` object available in execute(): interface Abs { searchTables(input: { query?: string; geography?: string; frequency?: "A"\|"S"\|"Q"\|"M"\|"W"\|"D"; limit?: number }): Promise<{ results: TableSummary[]; total: number }>; describeTable(table: string): Promise<{ table: TableSummary; dimensions: { id: string; position: number; optionCount: number; options?: { code: string; label: string\|null }[] }[]; keyFormat: string }>; searchOptions(input: { table: string; dimension: string; query: string; limit?: number }): Promise<{ options: { code: string; label: string\|null; parent?: string\|null }[]; total: number }>; getData(input: { table: string; select?: Record<string, string\|string[]>; startPeriod?: string; endPeriod?: string; lastN?: number; firstN?: number; maxRows?: number }): Promise<{ key: string; rows: { series: string; period: string; value: number\|null; unit?: string\|null }[]; rowsReturned: number; truncated: boolean; seriesMatched: number; fullDataUrl: string }>; } interface TableSummary { id: string; name: string\|null; seriesCount: number; frequencies: string[]; coverage: { from: string\|null; to: string\|null }; dimensions: string[]; family: string\|null; geography: string\|null; matchedOptions?: { dimension: string; code: string; label: string\|null }[] } // getData throws an Error whose message is JSON: { reason, dimensi	Run JavaScript in an isolated sandbox whose only capability is `abs`, a client with the same four verbs as this server (searchTables, describeTable, searchOptions, getData) and the same guarantees: every selection is verified against ABS before fetching. Use it for multi-series or multi-table analysis — fetch several series, compute growth rates, rank capitals, join tables — and `return` only the computed result, so large payloads never reach the conversation. No network beyond `abs`. Budgets: 10s CPU, 50 calls, 25s wall clock, 200KB result. Your code runs inside an async function; use `await`; console.log is captured. // The `abs` object available in execute(): interface Abs { searchTables(input: { query?: string; geography?: string; frequency?: "A"\|"S"\|"Q"\|"M"\|"W"\|"D"; limit?: number }): Promise<{ results: TableSummary[]; total: number }>; describeTable(table: string): Promise<{ table: TableSummary; dimensions: { id: string; position: number; optionCount: number; options?: { code: string; label: string\|null }[] }[]; keyFormat: string }>; searchOptions(input: { table: string; dimension: string; query: string; limit?: number }): Promise<{ options: { code: string; label: string\|null; parent?: string\|null }[]; total: number }>; getData(input: { table: string; select?: Record<string, string\|string[]>; startPeriod?: string; endPeriod?: string; lastN?: number; firstN?: number; maxRows?: number }): Promise<{ key: string; rows: { series: string; period: string; value: number\|null; unit?: string\|null }[]; rowsReturned: number; truncated: boolean; seriesMatched: number; fullDataUrl: string }>; } interface TableSummary { id: string; name: string\|null; seriesCount: number; frequencies: string[]; coverage: { from: string\|null; to: string\|null }; dimensions: string[]; family: string\|null; geography: string\|null; matchedOptions?: { dimension: string; code: string; label: string\|null }[] } // getData throws an Error whose message is JSON: { reason, dimensi	No	Yes	Yes	Yes
`feedback_form`Open a feedback form for the person, prefilled with your draft, so they can report a problem or suggest an improvement to this ABS connector — or flag something wrong in ABS's own data. Use it whenever the person wants to give feedback, or agrees when you offer after something went wrong. Fill in what you know from the conversation: kind, a one-line summary in their words, details, and the tool, table, selection and error involved. Never include personal information about anyone, and never fill in a contact email the person did not give you. This tool sends nothing: on hosts that show interactive views the person reviews, edits and sends the form themselves; elsewhere, follow the `next` field.	Open a feedback form for the person, prefilled with your draft, so they can report a problem or suggest an improvement to this ABS connector — or flag something wrong in ABS's own data. Use it whenever the person wants to give feedback, or agrees when you offer after something went wrong. Fill in what you know from the conversation: kind, a one-line summary in their words, details, and the tool, table, selection and error involved. Never include personal information about anyone, and never fill in a contact email the person did not give you. This tool sends nothing: on hosts that show interactive views the person reviews, edits and sends the form themselves; elsewhere, follow the `next` field.	No	Yes	Yes	No
`get_data`Fetch observations. `select` maps dimension ids to option codes or labels (several allowed); omitted dimensions match everything. The selection is verified live against ABS before fetching, so a call that succeeds always returns real data. Returns up to maxRows observations (default 500, most recent 12 periods per series unless a period range is given), a summary, and the URL for the complete pull. If an option or combination does not exist you are asked to choose from the valid ones.	Fetch observations. `select` maps dimension ids to option codes or labels (several allowed); omitted dimensions match everything. The selection is verified live against ABS before fetching, so a call that succeeds always returns real data. Returns up to maxRows observations (default 500, most recent 12 periods per series unless a period range is given), a summary, and the URL for the complete pull. If an option or combination does not exist you are asked to choose from the valid ones.	No	Yes	Yes	Yes
`search`Run JavaScript against the whole catalogue document — every table, its dimensions, coverage and small-dimension options — in an isolated sandbox with no network. Use it to answer questions the fixed verbs make awkward: 'which tables have both an SA2 geography and a quarterly frequency?', 'list every dimension name and how often it appears', 'find codelists whose labels mention rent'. Your code runs inside an async function with `catalogue` in scope; `return` a JSON-serialisable value; console.log output is captured. // The `catalogue` object available in search(): interface Catalogue { provenance: { runId: string; observedAt: string }; corpus: { tables: number; seriesConfirmed: number; seriesImpliedByMetadata: number; density: number }; tables: Record<string, { // keyed by table id, e.g. catalogue.tables.CPI id: string; name: string\|null; description: string\|null; seriesCount: number; frequencies: string[]; coverage: { from: string\|null; to: string\|null }; density: number\|null; family: string\|null; geography: string\|null; topics: string[]; dimensions: { id: string; position: number; codelist: string\|null; optionCount: number; literal: boolean }[]; }>; options: { literal: Record<string, Record<string, string\|null>>; // codelist id -> { code: label } for small codelists (<=64 options) branded: Record<string, number>; // large codelists -> option count (use abs.searchOptions in execute) }; }	Run JavaScript against the whole catalogue document — every table, its dimensions, coverage and small-dimension options — in an isolated sandbox with no network. Use it to answer questions the fixed verbs make awkward: 'which tables have both an SA2 geography and a quarterly frequency?', 'list every dimension name and how often it appears', 'find codelists whose labels mention rent'. Your code runs inside an async function with `catalogue` in scope; `return` a JSON-serialisable value; console.log output is captured. // The `catalogue` object available in search(): interface Catalogue { provenance: { runId: string; observedAt: string }; corpus: { tables: number; seriesConfirmed: number; seriesImpliedByMetadata: number; density: number }; tables: Record<string, { // keyed by table id, e.g. catalogue.tables.CPI id: string; name: string\|null; description: string\|null; seriesCount: number; frequencies: string[]; coverage: { from: string\|null; to: string\|null }; density: number\|null; family: string\|null; geography: string\|null; topics: string[]; dimensions: { id: string; position: number; codelist: string\|null; optionCount: number; literal: boolean }[]; }>; options: { literal: Record<string, Record<string, string\|null>>; // codelist id -> { code: label } for small codelists (<=64 options) branded: Record<string, number>; // large codelists -> option count (use abs.searchOptions in execute) }; }	No	Yes	Yes	No
`search_options`Find option codes by label text within one dimension of one table — e.g. a suburb name in a geography dimension. Returns codes to use in get_data's select.	Find option codes by label text within one dimension of one table — e.g. a suburb name in a geography dimension. Returns codes to use in get_data's select.	No	Yes	Yes	No
`search_tables`Find ABS statistical tables (dataflows) by topic words, geography level or frequency. Matches table names, topics and dimension names, and also option labels inside dimensions — a search for 'rent' finds CPI through its INDEX option 'Rents' and reports the match in matchedOptions. Census tables published at several geography levels are collapsed to one result with familyGeographies listing the others (use the geography filter to pick one). Every result has data. When the person describes a situation rather than a dataset, search for each thing it depends on (prices, wages, rents, population...). Start here, then describe_table.	Find ABS statistical tables (dataflows) by topic words, geography level or frequency. Matches table names, topics and dimension names, and also option labels inside dimensions — a search for 'rent' finds CPI through its INDEX option 'Rents' and reports the match in matchedOptions. Census tables published at several geography levels are collapsed to one result with familyGeographies listing the others (use the geography filter to pick one). Every result has data. When the person describes a situation rather than a dataset, search for each thing it depends on (prices, wages, rents, population...). Start here, then describe_table.	No	Yes	Yes	No
`submit_feedback`Send feedback about this ABS connector (or a report about ABS's own data) to its maintainers. Only call this after the person has seen the exact text and said to send it — prefer feedback_form, which lets them edit it first. Use about='abs' for wrong figures or broken behaviour in ABS's own data or API; set shareWithAbs only if the person agreed it may be passed on to ABS. Never include personal information about anyone, and include a contact email only if the person gave one for a reply. Returns a reference like FB-7Q2K9C to give the person.	Send feedback about this ABS connector (or a report about ABS's own data) to its maintainers. Only call this after the person has seen the exact text and said to send it — prefer feedback_form, which lets them edit it first. Use about='abs' for wrong figures or broken behaviour in ABS's own data or API; set shareWithAbs only if the person agreed it may be passed on to ABS. Never include personal information about anyone, and include a contact email only if the person gave one for a reply. Returns a reference like FB-7Q2K9C to give the person.	No	No	No	No

Details

Registry status: Active
Published: Sep 9, 2026
Updated: Sep 9, 2026
Website: https://abs-data-front-door.aicolab.workers.dev/⁠ (opens in a new tab)
Repository: https://github.com/AI-CoLab/abs-data-mcp⁠ (opens in a new tab)
Categories (suggested): Data and analyticsSuggested categories are assigned automatically from the registry text and may be wrong. Verified operators can correct them.
GDPR: Not declared

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