Statistics Canada MCP Server :: Web Data Service Interface

MCP SDK SDMX REST WDS REST v0.7.13 Python 3.11+ Stateless HTTP

Announcements:
NEW v0.7.9 — automated CI/CD: version bumps on push, landing announcement workflow
NEW v0.7.8 — tool-level request logging and /.well-known/mcp.json discovery
NEW v0.7.5 — SDMX get_sdmx_rows for inline data without context flood
• Listed on the MCP server registry

Abstract. This server exposes Statistics Canada’s Web Data Service (WDS) and SDMX REST API as a suite of Model Context Protocol (MCP) tools. Language models connect via the /mcp endpoint and gain structured access to over 7,000 Canadian statistical tables — labour force, GDP, inflation, demographics, health, environment, and more. The server operates in a fully stateless mode: no session state is retained between requests, enabling horizontal scaling and simplified deployment on platforms such as Render.

Connection Instructions

Add this server to your MCP client using the Streamable HTTP transport. No API key is required — Statistics Canada data is publicly available.

MCP Endpoint
https://mcp-statcan.onrender.com/mcp

Health Check
https://mcp-statcan.onrender.com/health

Claude Desktop (`claude_desktop_config.json`)

{
  "mcpServers": {
    "statcan": {
      "type": "http",
      "url": "https://mcp-statcan.onrender.com/mcp"
    }
  }
}

Claude Code (`.mcp.json`)

{
  "mcpServers": {
    "statcan": {
      "type": "http",
      "url": "https://mcp-statcan.onrender.com/mcp"
    }
  }
}

Note: This server is deployed on Render’s free tier. The first request after a period of inactivity may take 30–60 seconds while the instance spins up. Subsequent requests are fast.

Registered Tools (17)

All tools below are exposed over the /mcp endpoint. The hosted HTTP server runs in stateless mode — composite and SQLite database tools are intentionally omitted here. To use those, run the server locally over stdio (pip install statcan-mcp-server).

Tool Name	Category	Description
search_cubes_by_title	Discovery	Full-text keyword search across all StatCan tables, capped at 25 results
get_all_cubes_list	Discovery	Paginated inventory of all tables (100/page)
get_all_cubes_list_lite	Discovery	Lightweight paginated list, 1-hour TTL cache
get_cube_metadata	Metadata	Full table structure: dimensions, members, frequencies; summary mode caps members at 10
get_code_sets	Metadata	WDS attribute decoder tables (scalar type, UOM, frequency, status codes)
get_series_info	Series	Resolve dimension coordinates to vectorId, frequency, UOM
get_series_info_from_vector	Series	Look up series metadata by vectorId
get_bulk_vector_data_by_range	Vector	Fetch multiple vectors filtered by release-date range
get_changed_series_data_from_vector	Change Detection	Detect data changes for a vector since a given date
get_changed_series_data_from_cube_pid_coord	Change Detection	Detect changes for a specific series by coordinate
get_changed_cube_list	Change Detection	List all tables with data changes since a given date
get_changed_series_list	Change Detection	List all series with changes since a given date
get_sdmx_structure	SDMX	Data Structure Definition as JSON: dimension positions and codelists with hierarchy
get_sdmx_data	SDMX	Server-side filtered observations by productId + SDMX key string
get_sdmx_rows	SDMX	Inline tabular rows (up to 500) returned directly in the tool response
get_sdmx_vector_data	SDMX	Single vectorId observations via SDMX
get_sdmx_key_for_dimension	SDMX	Returns the full OR-key for a large dimension (avoids wildcard sampling errors)

Technical Specifications

Transport	Streamable HTTP (stateless) — MCP 2025-03-26 spec
Upstream APIs	Statistics Canada WDS REST + SDMX 2.1 REST
Authentication	None required (public data)
SSL Verification	Disabled (`VERIFY_SSL=False`) — StatCan certificate quirk
Max SDMX Rows	500 per `get_sdmx_data` call
Cache	1-hour TTL on `get_all_cubes_list_lite`
Python	3.11+ — asyncio, httpx, Starlette, Uvicorn
Install	`pip install mcp-statcan`
Source	github.com/Aryan-Jhaveri/mcp-statcan

Known Constraints & Notes

lastNObservations + startPeriod/endPeriod — cannot be combined; StatCan returns HTTP 406.
SDMX wildcard on large dimensions — . on dimensions with >30 codes returns sparse, unpredictable samples. Use get_sdmx_key_for_dimension for the full OR key instead.
vectorIds from metadata — get_cube_metadata returns member names but not vectorIds. Use get_series_info to resolve coordinates to vectorIds.
Geography OR key — known StatCan encoding bug for Geography dimension labels in OR-key syntax; use wildcard for Geography.

Data Attribution

All data returned by this server originates from Statistics Canada. Users are responsible for complying with Statistics Canada’s Open Licence when using or redistributing data obtained through this server. This MCP server is an independent project and is not affiliated with or endorsed by Statistics Canada or the Government of Canada.

Statistics Canada MCP Server