How do I install Statistics Canada MCP Server?

Copy the http config for Cursor, Claude Desktop, Claude Code, or VS Code on this page. It uses the publisher's install, not a PlugMCP proxy.

Does Statistics Canada MCP Server need an API key?

No required environment variable is listed on this record.

What transport does Statistics Canada MCP Server use?

Statistics Canada MCP Server is reached over HTTP.

When was Statistics Canada MCP Server last checked?

Last checked 2026-11-08. Access Statistics Canada data via the Web Data Services API

Statistics Canada MCP server

Statistics Canada MCP Server

MCP server and CLI for Statistics Canada's Web Data Service (WDS) and SDMX REST API. Gives any MCP client — Claude, Cursor, VS Code Copilot, Gemini — structured access to Canadian statistical data. Includes a standalone statcan CLI for direct downloads without an LLM.

Hosted on Render — no install required for most users. See Quick Start.

⚠️ LLMs may fabricate data. Always verify important figures against official Statistics Canada sources.

Quick Start
Examples
Setup by Client
How Claude.ai Uses This Server
MCP Prompts
statcan CLI
Features & Tools
Project Structure
Known Issues

Quick Start

Pick the option that fits you. You don't need to install anything for Option 1.

Option 1 — Use the hosted server (recommended)

Connect directly to the public server on Render. No uv, no terminal, no local setup.

Claude Desktop / Claude.ai

Open Settings → Connectors → Add Custom Connector
Name: mcp-statcan
URL: https://mcp-statcan.onrender.com/mcp
Save and restart

Claude Code

claude mcp add statcan --transport http https://mcp-statcan.onrender.com/mcp --scope global

The hosted server provides all WDS + SDMX tools. Database tools (SQLite) require local setup (Option 3) — they are intentionally excluded from the shared server.

Option 2 — Self-host HTTP (WDS + SDMX, no DB)

Run a local server with the same tools as the hosted version.

Step 1 — Install uv:

# macOS / Linux
curl -LsSf https://astral.sh/uv/install.sh | sh

# Windows (PowerShell)
powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"

Step 2 — Start the server:

uvx statcan-mcp-server --transport http
# Listening at http://localhost:8000

Step 3 — Connect your client to http://localhost:8000/mcp.

Option 3 — Full local setup (WDS + SDMX + SQLite)

Everything from Option 2, plus database tools for storing and querying data with SQL. Runs via stdio.

Step 1 — Install uv (same as above).

Step 2 — Configure your client with the stdio snippets in Setup by Client below.

uvx downloads and runs the server automatically on first use.

Option 4 — `statcan` CLI (no LLM needed)

Download StatCan data directly from the terminal. See statcan CLI.

uvx statcan-mcp-server        # installs the package
statcan search "labour force"
statcan metadata 14-10-0287-01                                    # run first to find dimension IDs
statcan download 14-10-0287-01 --key "1.1.1" --last 12 --output lfs.csv  # run `statcan metadata <pid>` first to find real dimension IDs

Examples

Chat examples

Dataset	Query	Demo	Source
Canada's Greenhouse Gas Emissions	"Create a simple visualization for greenhouse emissions for Canada as a whole over the last 4 years"	Chat	Table 38-10-0097-01
Canada's International Trade in Services	"Create a quick analysis for international trade in services for the last 6 months with a visualization"	Chat	Table 12-10-0144-01
Ontario Building Construction Price Index	"Generate a visualization for Ontario's Building Price index from Q4 2023 to Q4 2024"	Chat	Table 18-10-0289-01
Canadian Unemployment Dashboard	"Create a Canadian Unemployment Dashboard using statcan mcp"	Chat	Table 14-10-0287-01

Dashboard examples

Title	Link	Source
Canada's Critical Minerals Economy	Dashboard	Table 36-10-0708-01
Price of Everything: CPI Dashboard 2015–2026	Dashboard	Table 18-10-0004-01
Canada's Biomedical & Biotech Industries	Dashboard	Table 27-10-0297-01

Setup by Client

Hosted server (Option 1)

Claude Desktop — Settings → Connectors → Add Custom Connector

Name: mcp-statcan
URL: https://mcp-statcan.onrender.com/mcp

Claude Code

claude mcp add statcan --transport http https://mcp-statcan.onrender.com/mcp --scope global

Cursor — .cursor/mcp.json (project) or ~/.cursor/mcp.json (global):

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

VS Code (GitHub Copilot) — .vscode/mcp.json:

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

Self-hosted HTTP (Option 2)

Start uvx statcan-mcp-server --transport http first, then configure your client.

Most clients need mcp-proxy to bridge stdio ↔ HTTP. Claude Code connects natively.

Claude Desktop — Settings → Developer → Edit Config:

{
  "mcpServers": {
    "statcan": {
      "command": "uvx",
      "args": ["mcp-proxy", "--transport", "streamablehttp", "http://localhost:8000/mcp"]
    }
  }
}

Claude Code

claude mcp add statcan --transport http http://localhost:8000/mcp --scope global

Cursor / VS Code / Gemini — same mcp-proxy wrapper, pointing to http://localhost:8000/mcp.

Full local / stdio (Option 3)

Claude Desktop — Settings → Developer → Edit Config:

{
  "mcpServers": {
    "statcan": {
      "command": "uvx",
      "args": ["statcan-mcp-server", "--db-path", "/Users/<you>/.statcan-mcp/statcan_data.db"]
    }
  }
}

Pass --db-path with an absolute path. Claude Desktop overrides the subprocess HOME env var, which can break default path resolution.

Claude Code

claude mcp add statcan --scope global -- uvx statcan-mcp-server

Cursor / VS Code / Gemini — use uvx statcan-mcp-server as the stdio command.

How Claude.ai Uses This Server

Claude.ai (web) has no bash sandbox — it can't run shell commands. Instead, it uses MCP tools for discovery and its Python script tool to fetch data without bloating the context window.

The pattern:

1. MCP tools (small payloads — metadata only):
   search_cubes_by_title("labour force")  → productId
   get_sdmx_structure(productId=...)      → dimension layout + codes
   get_sdmx_key_for_dimension(...)        → OR key for large dimensions

2. Python script (data never enters context):
   url = "https://mcp-statcan.onrender.com/files/sdmx/<pid>/<key>?lastNObservations=12"
   → validate URL domain → write to ./statcan_<pid>.csv → print summary only

3. Follow-up script (analysis from local file):
   rows = list(csv.DictReader(open("./statcan_<pid>.csv")))
   → filter / sort / aggregate → print only the result

get_sdmx_data on the hosted server always returns a download_csv URL instead of inline data — data stays out of the context window regardless of response size.

Claude Code (bash sandbox) uses the statcan CLI instead:

statcan search "labour force"
statcan metadata 14-10-0287-01  # run first to find dimension IDs
statcan download 14-10-0287-01 --key "1.1.1" --last 12 --output ./lfs.csv  # run `statcan metadata <pid>` first to find real dimension IDs
awk -F',' 'NR>1 && $1=="Canada"' ./lfs.csv | sort -t',' -rn -k5 | head -10

MCP Prompts

The server ships five prompts accessible as slash commands in supported clients. Each has dual instructions — Claude Code (bash) and Claude.ai web (Python script).

Prompt	What it teaches
`/statcan-data-lookup`	End-to-end: search → structure → build key → fetch to local file → analyze
`/sdmx-key-builder`	SDMX key syntax: wildcards, OR keys, time parameters, download URL format
`/statcan-download`	Download a specific table: CLI commands + Python script alternative
`/statcan-explore`	Sample before committing: 3-period fetch, column layout, size estimate
`/statcan-vector-pipeline`	Multi-series download and cross-series comparison

Usage in Claude Code:

/statcan-data-lookup topic="consumer price index" analysis_goal="trend last 5 years"
/statcan-download product_id=18100004 last_n=24

statcan CLI

A standalone CLI for downloading StatCan data without an LLM. Outputs pipe-friendly CSV/JSON to stdout; progress and errors go to stderr.

Install:

pip install statcan-mcp-server   # or: uvx statcan-mcp-server (no install)

Commands:

statcan search <term>            Search tables by keyword
statcan metadata <product-id>    Show table structure (dimensions + members)
statcan download <product-id>    Download observations via SDMX
statcan vector <vector-id>...    Download one or more vector series
statcan codeset                  Show StatCan code definitions (UOM, frequency, etc.)

Common usage:

# Find a table
statcan search "consumer price index"
statcan search "labour force" --max-results 10 --format json

# Inspect structure before downloading
statcan metadata 18-10-0004-01
statcan metadata 18100004 --full        # show all dimension members

# Download data (run `statcan metadata <pid>` first to find real dimension IDs)
statcan download 18-10-0004-01 --key "1.1.1" --last 12 --output cpi.csv
statcan download 18-10-0004-01 --key "1.1.1" --start 2020-01 --end 2024-12
statcan download 18-10-0004-01 --key "1.1.1" --last 5 --dry-run   # preview SDMX URL

# Download by vector ID
statcan vector v41690973 --last 24 --output series.csv
statcan vector v41690973 v41690974 --last 12 --output multi.csv

# Decode numeric codes
statcan codeset --type uom
statcan codeset --type frequency --format json

Output formats: csv (default for download/vector), table (default for search/metadata/codeset), json

Pipe patterns:

# Top 10 by value (run `statcan metadata <pid>` first to find real dimension IDs)
statcan download 14-10-0287-01 --key "1.1.1" --last 1 --format csv \
  | awk -F',' 'NR>1' | sort -t',' -k5 -rn | head -10

# Extract unique geographies (run `statcan metadata <pid>` first to find real dimension IDs)
statcan download 14-10-0287-01 --key "1.1.1" --last 1 --format csv \
  | awk -F',' 'NR>1 {print $1}' | sort -u

# Chain search → download (run `statcan metadata <pid>` first to find real dimension IDs)
PID=$(statcan search "CPI" --format json | python3 -c "import sys,json; print(json.load(sys.stdin)[0]['Product ID'])")
statcan download $PID --key "1.1.1" --last 12 --output cpi.csv

For the complete CLI reference see cli.md.

Features & Tools

SDMX Tools — server-side filtered data fetch

Only the slice you request is returned. No downloading full tables.

Tool	Description
`get_sdmx_structure`	Dimension codelists + key syntax for a table. Call before `get_sdmx_data`.
`get_sdmx_data`	Filtered observations by `productId` + key. Returns a CSV download URL on the hosted server — data stays out of context.
`get_sdmx_vector_data`	Observations for a single vectorId via SDMX.
`get_sdmx_key_for_dimension`	All leaf member IDs for a large dimension as a ready-to-paste OR key. Use when a dimension has >30 codes (e.g. NOC, CMAs).

Key syntax (passed to get_sdmx_data):

"1.2.1" — Geography=1, Gender=2, Age=1
".2.1" — all geographies (wildcard), Gender=2, Age=1
"1+2.2.1" — Geography 1 or 2, Gender=2, Age=1

Note: Wildcard (.) on dimensions with >30 codes returns a sparse, unpredictable sample. Use get_sdmx_key_for_dimension to get the correct OR key.

WDS Discovery & Metadata

Tool	Description
`search_cubes_by_title`	Full-text search across all StatCan tables. AND logic, capped at 25 results.
`get_all_cubes_list` / `_lite`	Paginated table inventory (`offset`/`limit`, default 100/page).
`get_cube_metadata`	Dimension info, member lists, date ranges. `summary=True` caps members at 10 per dimension.
`get_code_sets`	Decode StatCan numeric codes (frequency, UOM, scalar factor, status).

WDS Series Resolution & Change Detection

Tool	Description
`get_series_info`	Resolve `{productId, coordinate}` pairs to vectorId + metadata.
`get_series_info_from_vector`	Resolve a vectorId to productId, coordinate, titles, frequency.
`get_changed_cube_list`	Tables updated on a specific date.
`get_changed_series_list`	Series updated on a specific date.
`get_changed_series_data_from_cube_pid_coord`	Data points that changed for a coordinate.
`get_changed_series_data_from_vector`	Data points that changed for a vectorId.
`get_bulk_vector_data_by_range`	Multiple vectors filtered by release date range.

Composite & Database Tools (local/stdio mode only)

These tools are not available on the hosted Render server — SQLite is per-process and not shared across users.

Tool	Description
`fetch_vectors_to_database`	Fetch vectors by reference period range and store to SQLite.
`store_cube_metadata`	Fetch full cube metadata into SQLite — browse all members and vectorIds with SQL.
`query_database`	Read-only SQL against the local SQLite database.
`create_table_from_data` / `insert_data`	Create or append to a table.
`list_tables` / `get_table_schema` / `drop_table`	Database utilities.

Typical workflow

Claude.ai web (hosted server):

1. search_cubes_by_title("unemployment rate")
   → productId e.g. 14100287

2. get_sdmx_structure(productId=14100287)
   → dimension positions + sample codes

3. get_sdmx_key_for_dimension(productId=14100287, dimension_position=3)
   → or_key for large dimensions

4. get_sdmx_data(productId=14100287, key=".2.1", lastNObservations=24)
   → returns download_csv URL

5. Python script: validate URL domain → write to ./statcan_14100287.csv → analyze → print summary

Claude Code (bash sandbox):

statcan search "unemployment rate"
statcan metadata 14100287
statcan download 14-10-0287-01 --key "1.1.1" --last 24 --output ./lfs.csv  # run `statcan metadata <pid>` first to find real dimension IDs
awk -F',' 'NR>1 && $1=="Canada"' ./lfs.csv | sort -t',' -rn -k5 | head -10

Project Structure

src/
├── api/
│   ├── cube/
│   │   ├── discovery.py         # search_cubes_by_title, get_all_cubes_list
│   │   ├── metadata.py          # get_cube_metadata
│   │   └── series.py            # get_series_info, change detection
│   ├── vector/
│   │   └── vector_tools.py      # vector series, bulk range fetch
│   ├── sdmx/
│   │   └── sdmx_tools.py        # get_sdmx_structure, get_sdmx_data, get_sdmx_key_for_dimension
│   ├── composite_tools.py       # fetch_vectors_to_database, store_cube_metadata (stdio only)
│   └── metadata_tools.py        # get_code_sets
├── cli/
│   ├── main.py                  # statcan CLI entry point (Typer app)
│   ├── output.py                # write_output, format helpers
│   └── commands/
│       ├── search.py            # statcan search
│       ├── metadata.py          # statcan metadata
│       ├── download.py          # statcan download
│       ├── vector.py            # statcan vector
│       └── codeset.py           # statcan codeset
├── db/                          # SQLite connection, schema, queries (stdio only)
├── models/                      # Pydantic input models
├── util/
│   ├── registry.py              # ToolRegistry — @decorator → MCP Tool schema
│   ├── truncation.py            # Response truncation + pagination guidance
│   ├── sdmx_json.py             # SDMX-JSON → tabular rows
│   └── cache.py                 # 1-hour TTL cache for cube list
├── config.py                    # BASE_URL, SDMX_BASE_URL, RENDER_BASE_URL, TRANSPORT, PORT
└── server.py                    # create_server(), MCP Prompts, HTTP routes (/files/sdmx/), CLI

Known Issues

Issue	Status	Workaround
"Unable to open database file" on Claude Desktop	Active	Pass `--db-path /Users/<you>/.statcan-mcp/statcan_data.db` in your config
SSL verification disabled	Active	`VERIFY_SSL = False` in all API calls — StatCan cert issues made this necessary
`lastNObservations` + `startPeriod`/`endPeriod` → 406	Active	Use one or the other, not both
OR syntax for Geography dimension unreliable	Active	Use wildcard (`.`) for Geography; OR works fine for other dimensions
Wildcard returns sparse data for large dimensions	Mitigated	Use `get_sdmx_key_for_dimension` to get the full OR key (e.g. NOC, CMAs)
Context overflow may cause data fabrication	Mitigated	Hosted server returns `download_csv` URL — data processed via script, not context

Statistics Canada MCP Server

Add this server

Host a copy with our keys and logs.

Server facts

Tools

Questions

How do I install Statistics Canada MCP Server?

Does Statistics Canada MCP Server need an API key?

What transport does Statistics Canada MCP Server use?

When was Statistics Canada MCP Server last checked?

Documentation

Statistics Canada MCP Server

Table of Contents

Quick Start

Option 1 — Use the hosted server (recommended)

Option 2 — Self-host HTTP (WDS + SDMX, no DB)

Option 3 — Full local setup (WDS + SDMX + SQLite)

Option 4 — `statcan` CLI (no LLM needed)

Examples

Chat examples

Dashboard examples

Setup by Client

Hosted server (Option 1)

Self-hosted HTTP (Option 2)

Full local / stdio (Option 3)

How Claude.ai Uses This Server

MCP Prompts

statcan CLI

Features & Tools

SDMX Tools — server-side filtered data fetch

WDS Discovery & Metadata

WDS Series Resolution & Change Detection

Composite & Database Tools (local/stdio mode only)

Typical workflow

Project Structure

Known Issues

Add this server

Host a copy with our keys and logs.

Server facts

Tools

Questions

How do I install Statistics Canada MCP Server?

Does Statistics Canada MCP Server need an API key?

What transport does Statistics Canada MCP Server use?

When was Statistics Canada MCP Server last checked?

Documentation

Statistics Canada MCP Server

Table of Contents

Quick Start

Option 1 — Use the hosted server (recommended)

Option 2 — Self-host HTTP (WDS + SDMX, no DB)

Option 3 — Full local setup (WDS + SDMX + SQLite)

Option 4 — statcan CLI (no LLM needed)

Examples

Chat examples

Dashboard examples

Setup by Client

Hosted server (Option 1)

Self-hosted HTTP (Option 2)

Full local / stdio (Option 3)

How Claude.ai Uses This Server

MCP Prompts

statcan CLI

Features & Tools

SDMX Tools — server-side filtered data fetch

WDS Discovery & Metadata

WDS Series Resolution & Change Detection

Composite & Database Tools (local/stdio mode only)

Typical workflow

Project Structure

Known Issues

Option 4 — `statcan` CLI (no LLM needed)