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Statistics Canada MCP Server logo
Health: ActiveRecent health check succeeded.Last checked 9/22/2026, 12:16:06 PM

Statistics Canada MCP Server

User RatingsBe the first to rate and review this MCP server!
View Repository6 GitHub StarsTotal stargazers on GitHub for the source repository (6 stars).Visit Website
statistics-canadasdmxdata-platformsqliteresearch

Queries Statistics Canada tables, metadata, SDMX observations, changed data, and local SQLite datasets through MCP.

Quick Install

Automated & IDE Setup

Copy the AI prompt to install this server into Claude Code, Cursor, or another agent β€” or use 1-click editor setup below.

Add to CursorAdd to VS Code
Automated check passedβ€” started and listed 25 tools correctly (3d ago).
Manual Client & Custom JSON ConfigExpand JSON β–Ύ

Client Config & Setup

Choose your client or environment
Target File:~/Library/Application Support/Claude/claude_desktop_config.json
claude_desktop_config.json
{
  "mcpServers": {
    "statistics-canada-mcp-server": {
      "command": "uvx",
      "args": [
        "statcan-mcp-server"
      ]
    }
  }
}

πŸ’‘ Paste the JSON block into your client's configuration file under mcpServers, then restart the application.

Install Tool Schemas (25) Directory Badge Claim listing AlternativesπŸ“Š More in Data Platforms

Overview

Statistics Canada MCP Server MCP server exposes Statistics Canada's Web Data Services and SDMX REST APIs as MCP tools. It supports table discovery, metadata lookup, dimension-code exploration, vector and time-series retrieval, change tracking, and data storage in SQLite for local deployments. Use it when an agent needs Canadian statistical data with table, product, vector, coordinate, or SDMX source references. A hosted HTTP endpoint is available, while local stdio mode adds the SQLite database tools.

Use cases

β€’Search Statistics Canada tables by English or French title
β€’Fetch filtered SDMX observations for selected dimensions and periods
β€’Track tables or series updated on a specified date
β€’Store multi-series data in SQLite for SQL analysis
β€’Build charts or widgets from inline observation rows

Key features

β€’Statistics Canada WDS and SDMX access
β€’Cube, dimension, codelist, and series discovery
β€’Vector and time-series retrieval
β€’Changed-data and release-date queries
β€’Persistent SQLite storage and read-only SQL
β€’Source-reference guidance for returned data

Capabilities & Tool Schemas (25) ~7.4k tokensApproximate context cost of this server’s tool schemas (~4 chars/token), before any tool is called. Actual usage depends on your client and model.Verified live Verified liveCaptured by calling this server’s live tools/list endpoint.

Inspect callable tools, capabilities, and parameters exposed to AI agents by Statistics Canada MCP Server.

get_code_sets

Retrieves definitions for various code sets used by the API (e.g., frequency, units of measure). Corresponds to: GET /getCodeSets Returns: Dict[str, Any]: Dictionary containing code set definitions (scalar, frequency, etc.). Raises: httpx.HTTPStatusError: If the API returns an error status code. ValueError: If the API response format is unexpected. Exception: For other network or unexpected errors. IMPORTANT: In your final response to the user, you MUST cite the source of your data. For code sets, this means specifying which code set table or definition is being used.

get_all_cubes_list

Provides a complete inventory of data tables available via the API, including dimension-level details. Disables SSL Verification. Corresponds to: GET /getAllCubesList Results are paginated. Default returns first 100 cubes. Use offset/limit to page through. Prefer search_cubes_by_title if you know what you're looking for. IMPORTANT: In your final response to the user, you MUST cite the source of your data. For cubes, this means including the ProductId (pid) and the Title.

get_all_cubes_list_lite

Provides a complete inventory of data tables available via the API, excluding dimension or footnote information (lighter version). Disables SSL Verification. Corresponds to: GET /getAllCubesListLite Results are paginated. Default returns first 100 cubes. Use offset/limit to page through. Prefer search_cubes_by_title if you know what you're looking for. IMPORTANT: In your final response to the user, you MUST cite the source of your data. For cubes, this means including the ProductId (pid) and the Title.

search_cubes_by_title

Searches for data cubes/tables where the English or French title contains the provided search term (case-insensitive). Returns a list of matching cubes in the 'lite' format (excluding dimensions/footnotes). Multiple keywords use AND logic (e.g., "tobacco smoking age" finds cubes containing ALL three words). Results are capped at max_results (default 25). IMPORTANT: In your final response to the user, you MUST cite the source of your data. For cubes, this means including the ProductId (pid) and the Title. Raises: httpx.HTTPStatusError: If the underlying API call fails. Exception: For other network or unexpected errors during the fetch.

get_cube_metadata

Retrieves detailed metadata for a specific data table/cube using its ProductId. Includes dimension info, titles, date ranges, codes, etc. Disables SSL Verification. Corresponds to: POST /getCubeMetadata Start with summary=True (default). The summary strips noise (French translations, archive codes, footnotes) and shows only 3 sample members per dimension with _next_steps guidance. Safe for all context window sizes. Set summary=False only if you need the full raw member list or all API fields. To browse dimension codes for get_sdmx_data key construction, use get_sdmx_structure. To resolve a coordinate to a vectorId, use get_series_info. Returns: Dict[str, Any]: The metadata object for the specified cube on success. Raises: httpx.HTTPStatusError: If the API returns an error status code. ValueError: If the API response format is unexpected or status is not SUCCESS. Exception: For other network or unexpected errors. IMPORTANT: In your final response to the user, you MUST cite the source of your data. For cubes, this means including the ProductId (pid) and the Title.

get_changed_series_data_from_cube_pid_coord

Retrieves changed series data (data points that have changed) using Cube ProductId and Coordinate string. Coordinates are automatically padded to 10 dimensions. Disables SSL Verification. Corresponds to: POST /getChangedSeriesDataFromCubePidCoord Returns: Dict[str, Any]: A dictionary containing the changed series data object. Raises: httpx.HTTPStatusError: If the API returns an error status code. ValueError: If the API response format is unexpected or status is not SUCCESS. Exception: For other network or unexpected errors. IMPORTANT: In your final response to the user, you MUST cite the source of your data. For changed series data, this means including the VectorId, ProductId (pid), and Coordinate.

How Statistics Canada MCP Server works

What Statistics Canada MCP Server MCP server does

Statistics Canada MCP Server MCP server gives MCP clients structured access to Statistics Canada datasets through the Web Data Services API and SDMX REST API. It can search table titles in English or French, list available cubes, retrieve cube metadata, resolve series identifiers, fetch observations, and identify tables or series updated on a particular date.

The server also supports local data workflows. A local deployment can fetch multiple vectors into SQLite, persist full cube metadata in normalized tables, create tables from returned data, append rows, inspect schemas, list tables, run read-only SQL queries, and drop tables. The hosted deployment provides WDS and SDMX tools but does not include the SQLite tools.

How it works

A typical discovery flow starts with search_cubes_by_title, followed by get_cube_metadata or get_sdmx_structure. Metadata exposes dimensions, member codes, date ranges, and series information. For large dimensions, get_sdmx_key_for_dimension produces a ready-to-use OR key containing leaf member IDs.

Once the required dimensions are known, get_sdmx_data retrieves a filtered slice using a dot-separated SDMX key, while get_sdmx_vector_data handles a known vector. get_sdmx_rows is intended when rows must be embedded directly into an artifact or widget. Time filters can use a reference-period range or a count of recent observations, but those modes cannot be combined.

For multi-series work, the Statistics Canada MCP Server MCP server can fetch vectors directly into a named SQLite table. This avoids returning every observation to the model context and allows subsequent SQL analysis. Release-date queries use get_bulk_vector_data_by_range; reference-period queries use the SDMX tools instead.

Setup and configuration

The repository documents a hosted endpoint at https://mcp-statcan.onrender.com/mcp, which can be added as a custom HTTP connector. It also documents local HTTP startup with:

bash
uvx statcan-mcp-server --transport http

For full local functionality, run the package through stdio:

bash
uvx statcan-mcp-server

A custom SQLite location can be supplied with --db-path when configuring a local client. The project requires Python 3.10 or newer. No API key or other credential is specified in the supplied material.

Tools and capabilities

The Statistics Canada MCP Server MCP server includes tools for:

  • Listing code-set definitions and decoding numeric frequency, scalar-factor, and unit codes.
  • Searching or listing cubes, including lightweight and dimension-rich inventory formats.
  • Reading cube and series metadata by product ID, coordinate, or vector ID.
  • Fetching current, changed, bulk, vector, and SDMX observations.
  • Inspecting SDMX structures, codelists, dimension positions, and leaf-member keys.
  • Tracking cubes and series changed on a specified date.
  • Persisting vector data and cube metadata in SQLite for local analysis.
  • Creating, inserting into, querying, inspecting, listing, and dropping SQLite tables.

Limitations and notes

Responses have context and size limits. SDMX row results are capped at 500 rows, and large vector responses should be narrowed or paginated. Wildcards on dimensions with more than 30 codes may return sparse samples; explicit member IDs joined with + are recommended for those dimensions. StatCan rejects requests that combine lastNObservations with startPeriod or `endPeriod.

Several tools disable SSL verification according to their documented behavior. The local SQLite database is persistent, and table-dropping is irreversible. Read-only SQL is supported by query_database; untrusted SQL should not be passed to it.

Data provenance is part of the tool contract. Cube results should identify the ProductId and title; series results should include the vector ID, product ID, and coordinate; SDMX results should include the _sdmx_url, product ID or vector ID, and key where applicable. For authoritative verification, consult Statistics Canada at https://www.statcan.gc.ca/ and the documented WDS and SDMX sources: https://www.statcan.gc.ca/eng/developers/wds and https://www150.statcan.gc.ca/t1/wds/sdmx/statcan/rest/.

Read the full README β†’View source on GitHub β†’

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Adoption & maintenance

Factual signals from GitHub, npm, and our automated checks β€” not a rating.

GitHub stars
6
Stargazers on the source repository.
Last commit
5d ago
Most recent push to the default branch.
Availability
100%
Our rolling endpoint + install checks that succeeded.
Install check
Passed
Our sandbox started it and listed its tools.
Tools exposed
25
Callable tools this server registers over MCP.
Directory activity
4 views
Config copies, upvotes, and views on AllMCPs.

Reviews

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Frequently Asked Questions about Statistics Canada MCP Server

Run `uvx statcan-mcp-server` for the local stdio server, or run `uvx statcan-mcp-server --transport http` for local HTTP mode. The README also documents a hosted endpoint.

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Technical Specs & Signals

CategoryπŸ“ŠData Platforms
PricingFree
More technical detailsExpand β–Ύ
TransportSTDIO
RuntimePython
AuthNo auth required
LicenseMIT
ClientsClaude Desktop, Cursor
Last updatedSep 19, 2026
11/16 checks healthy over the last 45d
Views4
Unique ViewsTotal visits recorded for this listing page on AllMCPs.
Installs0
Installs & Copy ActionsTotal times users copied install commands or configuration snippets for this server.
GitHub stars6
GitHub Star CountTotal stargazers on GitHub representing community popularity (6 stars).
Last commit5d ago
Last Repository CommitThe most recent commit or push recorded for this server's GitHub repository.Last commit on Sep 19, 2026
71Quality signal: Great Β· 71/100How this signal is calculated β–Ύ
Server availability25/25
Verified ownership10/20
Documentation & tools30/30
Adoption & activity5/15
Community engagement1/10

A guidance signal from public completeness & health data β€” not a user rating. New listings start lower and rise as they add docs, get verified, and grow adoption. Signals we can't observe for a listing are skipped, not counted against it.

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Scanned 2d ago via OSV.dev Β· statcan-mcp-server (PyPI)

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