statcan-mcp
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {
"listChanged": true
} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| search_tablesA | Keyword search across all ~8,200 Statistics Canada data tables (CPI, GDP, labour force, housing, population...). Returns product IDs to explore with get_table_metadata. |
| get_table_metadataA | Structure of a Statistics Canada table: its dimensions and their members with member IDs. Large dimensions are truncated — pass member_filter (e.g. 'gasoline') to find specific members. Use the member IDs with get_data_by_coordinate. |
| get_data_by_vectorsA | Fetch observations for up to 10 Statistics Canada vector IDs (a vector uniquely identifies one time series, e.g. v41690973 = CPI all-items Canada). Give a date range, or latest_n most recent periods (default 12). |
| get_data_by_coordinateA | Fetch observations by choosing one member ID per dimension of a table (get them from get_table_metadata). Example: table 18100004 with member_ids [2, 2] = CPI, Canada, all-items. |
| get_series_infoA | What is this vector? Returns the series title, source table, and coordinate for a vector ID. |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 5 tools
Each tool has a distinct role: searching tables, inspecting metadata, fetching data via vectors, fetching data via coordinates, and identifying series. The two data-fetch tools are clearly separated by their ID system, with descriptions explaining the difference.
All tool names use a consistent verb_noun pattern in snake_case (search_tables, get_table_metadata, get_data_by_vectors, get_data_by_coordinate, get_series_info). The verbs and nouns are clear and uniform in style.
Five tools is well-scoped for a statistical data server, covering discovery, schema exploration, and data extraction without unnecessary redundancy or bloat.
The tools cover the full workflow from finding a table to retrieving specific data values. A minor gap exists in the lack of a direct table-level description tool, but get_table_metadata provides sufficient structural information to work around this.