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Canada Post MCP Server

Canada Post MCP Server

by richardsondx
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Hybrid

find_post_office

Locate Canada Post offices near a city, place, or postal code and get real addresses, including recorded downtown Toronto results when API credentials are unavailable.

Instructions

Find Canada Post post offices near a place or postal code. Each result has a real address. Without API credentials it uses a recorded directory of real downtown Toronto offices, labelled as recorded data.

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": "find_post_office"
  }
}

Input Schema

NameRequiredDescriptionDefault
queryNoPlace or city name, e.g. Toronto.
radius_kmNoSearch radius in kilometres. Default 5.
postal_codeNoCanadian postal code near the search area, e.g. M5G 1N6.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.8/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does real work: it discloses that every result has a real address and, critically, that without API credentials the tool silently falls back to a recorded directory of downtown Toronto offices that is labelled as recorded data. That is a meaningful data-provenance and coverage caveat an agent would otherwise not know. It does not mention result counts, pagination, or failure modes when a location is outside Toronto.

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, each carrying load: what it finds, what the results contain, and the credential-dependent data caveat. Nothing is redundant and the core purpose is front-loaded.

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

Completeness4/5

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

For a simple three-parameter lookup with no output schema, the description covers purpose, result shape (real addresses), and the important fallback caveat. Only minor operational details like expected result volume or geographic limits of the fallback directory are left implicit.

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%, so the schema already documents query, radius_km (with its default of 5), and postal_code with examples. The description only reinforces that a place or postal code can drive the search and adds no format or precedence details beyond the schema, so the baseline 3 applies.

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

Purpose4/5

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

The description opens with a specific verb and resource: "Find Canada Post post offices near a place or postal code." That is unambiguous and clearly distinct from the sibling tools (rates, mail listing, tracking), though it never explicitly contrasts itself with them.

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

Usage Guidelines3/5

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

Usage is implied by the phrase "near a place or postal code," which tells an agent the two natural inputs. There is no explicit when-to-use/when-not guidance or routing to alternatives, but for a narrow, self-evident lookup tool that is a minor gap.

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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