Statistics Canada MCP Server

list_tables

Retrieve all user-created table names from the Statistics Canada SQLite database to inspect and clean outdated tables.

Instructions

Lists all user-created tables in the SQLite database.

Returns: Dict[str, Any]: Dictionary containing a list of table names or an error message.

IMPORTANT: The database is persistent. Use this to check for old tables that might need cleaning.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "list_tables"
  }
}

Input Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.7.15Aug 6, 2026

TDQS

A4.5/5.0

Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries full burden; it adds key context that the database is persistent and that only user-created tables are returned, with an error message on failure. It implies a read-only operation by the verb 'Lists' but does not explicitly state non-destructive behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three short sentences plus a return type declaration; every sentence earns its place. The important note about persistence and cleaning is relevant rather than filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a zero-parameter, no-output-schema tool, the description covers the result shape, the scope (user-created tables), and an important operational caution. No critical information is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has no parameters, so the description needs no parameter details. The baseline of 4 applies, and the description adds sufficient contextual information for a parameterless tool.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses the specific verb 'Lists' and identifies the resource as 'user-created tables in the SQLite database,' clearly distinguishing it from schema/drop/query siblings. It also states the return type, making the tool's core function unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It explicitly says to use this for checking old tables that might need cleaning, providing a concrete use case. However, it does not mention alternatives or when not to use it, so it lacks explicit exclusion guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.