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@pipeworx/mcp-statcan

v0.2.4

Published

StatCan MCP — Statistics Canada (StatCan) via the Web Data Service (WDS).

Readme

StatCan — Statistics Canada

Canada's national statistical office, via the free, keyless Web Data Service (WDS, www150.statcan.gc.ca/t1/wds/rest). Covers the full cube (table) catalogue — population, CPI/inflation, unemployment, GDP, trade, agriculture, and every other official Canadian series — plus headline indicators pre-resolved to a vector id.

Part of Pipeworx — an MCP gateway connecting AI agents to 1715+ live data sources. This is an independent, unofficial integration — not affiliated with, endorsed by, or published by the upstream provider.

Two access patterns

  1. Friendly / vector-based — statcan_indicator (cpi, unemployment, gdp, population by geography) and statcan_series (any series by numeric vector id, FRED-style).
  2. Cube-based — statcan_list_cubes (catalogue), statcan_cube_metadata (dimensions + members for one cube), statcan_cube_vectors (enumerate the actual vector ids for a cube), statcan_cube_data (latest N observations at a coordinate), statcan_table (whole table / filtered slice — see below), statcan_changed_series (daily change feed), statcan_csv_url (full-table CSV download link, live upstream URL, never fetches).

statcan_table — whole-table lookup (fleet #2507)

statcan_cube_data answers ONE coordinate per call and statcan_csv_url only hands back a download URL — neither can answer "the whole table" or "every province at once" in one call, which is what most repeat callers actually want (60d: statcan rep3 146, #2 repeat-demand cluster in the catalog; no_match evidence: 42100037 child-care-difficulty coords fetched one at a time, 34100035 hydro-electric Quebec, 32100113 milk sold off farms, 98100353 2021 Census religion by province).

statcan_table answers from a curated set of high-demand StatCan tables (statcan_table_rows, refreshed weekly by workers/data-pipeline/src/datasets/statcan.ts from StatCan's own getFullTableDownloadCSV export), not the live WDS API:

statcan_table({ product_id: 42100037 })
// -> every coordinate, every ref_date, member labels (e.g. { "Statistics":
//    "Percentage of children", "Type of difficulty encountered...": "..." }),
//    in one call. Paged (limit/page) past 1000 rows.

statcan_table({ product_id: 32100113, geo: "Quebec", ref_date_from: "2023-01" })

Coverage is curated, not universal. Calling statcan_table on a product_id that isn't cached REFUSES with a clear error naming the currently-cached ids — it never silently returns an empty result. For anything outside that set, use statcan_cube_data (per-coordinate, live) or statcan_csv_url (raw CSV, live) instead. The wave-1 list (16 tables — see statcan.ts for the full rationale) covers the tables with verified repeat demand; adding a new table to the ingest list needs no migration (see next paragraph).

Schema is generic on purpose. StatCan's per-table CSV carries a fixed set of metadata columns (REF_DATE, GEO, DGUID, VECTOR, COORDINATE, VALUE, STATUS, SYMBOL, TERMINATED, DECIMALS, UOM, UOM_ID, SCALAR_FACTOR, SCALAR_ID) plus however many table-specific dimension-label columns the table declares (e.g. "Statistics", "Type of difficulty encountered..." for 42100037) — those vary per table, so they're captured into a members jsonb column rather than a per-table relational schema.

Every response carries data_as_of (from the ingestion pipeline's pipeline_state.last_success_at for that table) and a licence field. Licence: Statistics Canada Open Licence (statcan.gc.ca/en/reference/licence) — explicitly permits reproduction, redistribution and sale of the Information, conditioned on source acknowledgment ("Source: Statistics Canada, name of product, reference date...") and not implying StatCan endorsement. No personal data is stored — every row is an aggregate statistic.

Table number → vector id, in two calls

Every StatCan question starts with a table (e.g. "32-10-0121-01", the egg production table, or its 8-digit form 32100121). Neither the table number nor statcan_cube_metadata hands you a vector id directly — metadata only gives dimensions and their member lists. Use statcan_cube_vectors to bridge that:

statcan_cube_vectors({ product_id: "32100121", filters: { GEO: "Canada" } })
// -> rows: [{ vector_id: 61133, coordinate: "1.1.0.0.0.0.0.0.0.0",
//            members: { Geography: "Canada", "Production and disposition": "Average number of layers" },
//            frequency: "Monthly", terminated: false, series_title: "Canada;Average number of layers" }, ...]

statcan_series({ vector_id: "61133" })
// -> the actual observations

filters keys match by case-insensitive substring against the cube's dimension names (so GEO matches Geography); values match by substring against member names. Dimensions left unfiltered include every member of that dimension — for a cube with many dimensions that's a large cross-product, so page with limit/page (default 100/page, max 500) rather than pulling everything at once. total_combinations and has_more/next_page in the response tell you whether you're seeing all of it.

statcan_cube_metadata does not return vector ids — it only lists dimensions and members, which is why statcan_cube_vectors exists.

product_id accepts either form

  • The 8-digit WDS product id: 32100121
  • The public table number: 32-10-0121-01 (StatCan's NN-NN-NNNN-NN display format — the tool strips the dashes and drops the trailing 2-digit suffix)

Auth

None. Fully keyless — StatCan WDS has no rate-limit key or auth header.

Common pitfalls

  • statcan_cube_data needs a coordinate you already know. If you don't have one, get it from statcan_cube_vectors first — don't hand-build a coordinate from statcan_cube_metadata's member list and guess.
  • A wide table has thousands of combinations. Always filter by at least one dimension (most often GEO) before enumerating a table you haven't seen — otherwise you'll be paging for a long time.
  • terminated: true on a statcan_cube_vectors row means that series has stopped publishing; the cube's cube_start_date/cube_end_date describe the whole table's range, not any one series' actual last observation.

Quick Start

Add to your MCP client (Claude Desktop, Cursor, Windsurf, etc.):

{
  "mcpServers": {
    "statcan": {
      "url": "https://gateway.pipeworx.io/statcan/mcp"
    }
  }
}

What this endpoint actually serves

tools/list at https://gateway.pipeworx.io/statcan/mcp returns the tools in the table above plus the shared Pipeworx meta-tools — ask_pipeworx, discover_tools, search_within, remember/recall and the rest of the gateway-wide set. So the tool count you see is larger than this table: a single-pack endpoint currently lists roughly 30 shared tools alongside the pack's own. The connection's initialize response states its exact scope, and is the authoritative answer for a given day.

This is deliberate, not multiplexing by accident. The meta-tools are what let a scoped connection answer a question this pack does not cover — via ask_pipeworx, which routes across the whole catalog — without you adding a second MCP server. There is currently no way to mount a pack endpoint without them; if the extra schemas cost you more context than the routing is worth, connect to the full gateway once rather than to several pack endpoints.

Or connect to the full Pipeworx gateway to get every pack's tools listed directly, instead of just this one's:

{
  "mcpServers": {
    "pipeworx": {
      "url": "https://gateway.pipeworx.io/mcp"
    }
  }
}

Both URLs reach the same gateway and the same 1715+ data sources. The only difference is which pack's tools are listed directly; ask_pipeworx reaches all of them from either one.

No MCP client? Call it over HTTP

curl -X POST https://gateway.pipeworx.io/v1/tools/statcan_indicator \
  -H 'Content-Type: application/json' \
  -d '{"indicator":"cpi"}'

No account needed for the first calls. Inspect any tool: GET https://gateway.pipeworx.io/v1/tools/statcan_indicator. Find one: POST https://gateway.pipeworx.io/v1/tools/search_packs with {"query":"..."}.

Standalone (no gateway account)

This package also runs as a local stdio MCP server — no Pipeworx account, no gateway round-trip:

{
  "mcpServers": {
    "statcan": {
      "command": "npx",
      "args": ["-y", "@pipeworx/mcp-statcan"]
    }
  }
}

Or run it directly to confirm it starts:

npx -y @pipeworx/mcp-statcan

It speaks MCP over stdin/stdout and answers initialize/tools/list/tools/call for only this pack's tools — none of the shared meta-tools the gateway connection above adds. Same source, same tools, no ask_pipeworx routing.

Using with ask_pipeworx

Instead of calling tools directly, you can ask questions in plain English — this works on the pack endpoint above as well as on the full gateway:

ask_pipeworx({ question: "your question about Statcan data" })

The gateway picks the right tool and fills the arguments automatically.

More

License

MIT