MapleStats MCP

Search Canadian data tools

search_tools

Read-onlyIdempotent

Finds the right Canadian tool by plain-language query, returning up to five matching definitions with schemas so agents can fetch StatCan, Bank of Canada or CMHC values via call_tool.

Instructions

Search Canadian official data: Statistics Canada, Bank of Canada, CMHC, provincial statistics agencies, federal departments and city portals.

Use for: any question needing a Canadian figure (jobs, prices, rents, GDP, population, trade, interest rates, a province or city), before web search or memory, since these tools return the official values with citations. Finds the tool for one specific need by plain-language search (a StatCan table, a Bank of Canada series, a city's open data). Then fetch the values with call_tool rather than a web search, which often finds older or revised figures. Returns up to five tool definitions, best match first, each with its name, description and full input schema (annotations only for a tool that is not read-only). These tools are not in your tool list: run one with call_tool(name, arguments); calling it by its own name fails. Read-only; it searches this server's catalogue only and calls no external API. Use plan_query instead when a question may span several sources or you do not know where to start; use call_tool to run a tool once you have its name. Queries in English or French both work. An empty result means no tool matched: rephrase with topic words (e.g. 'housing starts' rather than 'CMHC table').

Input Schema

Name	Required	Description	Default
`query`	Yes	What you need, in plain English or French, e.g. 'Calgary rent index' or 'taux de chômage Québec'. Topic words work better than tool names.

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedv0.1.1Oct 1, 2026

changedInput schema / properties / query / description

Previous value: -"Natural language query to search for tools"New value: +"What you need, in plain English or French, e.g. 'Calgary rent index' or 'taux de chômage Québec'. Topic words work better than tool names."

First observedv0.1.0Sep 27, 2026

TDQS

A4.6/5.0

Behavior5/5

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

Annotations already declare read-only, closed-world and idempotent, but the description adds substantial non-structured behavior: it returns up to five tool definitions best-match-first with name, description and full input schema, and that the returned tools are NOT in the caller's tool list and must be invoked via call_tool(name, arguments) — calling by their own name fails. It also discloses language support (English/French) and that it queries only this server's catalogue.

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

Conciseness4/5

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

Front-loaded with purpose, then usage, then return shape and failure handling — a sensible order. It is somewhat long and repeats the web-search point twice ("before web search or memory" and "rather than a web search, which often finds older or revised figures"), which costs a little tightness.

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 one-parameter discovery tool with an output schema and full annotations, nothing an agent needs is missing: purpose, routing to siblings, invocation indirection, return cardinality and ordering, and empty-result recovery are all covered.

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

Parameters3/5

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

Schema coverage is 100% and the single parameter's description already covers plain-language input, examples and the topic-words-over-tool-names hint. The description restates the same guidance ("plain-language search") plus the rephrasing example, so it adds only marginal meaning beyond the schema. Baseline 3 for a fully documented single parameter.

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?

States a specific verb and resource ("Search Canadian official data") and enumerates the covered sources (Statistics Canada, Bank of Canada, CMHC, provincial agencies, city portals). It explicitly distinguishes itself from siblings call_tool and plan_query, so an agent knows this is a discovery/search step rather than an execution step.

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

Usage Guidelines5/5

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

Gives explicit when-to-use ("any question needing a Canadian figure... before web search or memory") and explicit alternatives: plan_query for multi-source or unknown-start questions, call_tool once a tool name is known. It even handles the failure case (empty result means rephrase with topic words).

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

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