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Alko MCP Server

Alko MCP Server

by markusl
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Hybrid

List Alko Stores

list_stores
Read-onlyIdempotent

Retrieve Alko store locations in Finland with city filtering. Get store IDs, names, addresses, and postal codes for all ~360 stores.

Instructions

List all ~360 Alko stores in Finland. Filter by city name. Returns: store id, name, address, city, postal code.

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_stores"
  }
}

Input Schema

NameRequiredDescriptionDefault
cityNoFilter by city name (e.g., "Helsinki", "Tampere")
limitNoMaximum number of stores to return

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already provide readOnlyHint=true, destructiveHint=false, idempotentHint=true, and openWorldHint=false. The description adds valuable context beyond annotations by specifying the approximate dataset size (~360 stores), the geographic scope (Finland), and the return format (store id, name, address, city, postal code). It doesn't contradict annotations and provides useful operational context.

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?

The description is extremely concise (two sentences) and front-loaded with the core purpose. Every word earns its place: the first sentence establishes scope and filtering, the second specifies return format. No wasted words or redundant information.

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 read-only list tool with comprehensive annotations and 100% schema coverage, the description provides good context about dataset size, geographic scope, and return format. The main gap is the lack of output schema, but the description compensates by explicitly listing return fields. It could be more complete by mentioning pagination behavior or result ordering.

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 description coverage is 100%, with both parameters (city and limit) fully documented in the schema. The description mentions filtering by city name but doesn't add any semantic details beyond what the schema already provides (e.g., city parameter examples or limit behavior). Baseline 3 is appropriate when the schema does the heavy lifting.

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 clearly states the verb ('List') and resource ('all ~360 Alko stores in Finland'), specifies the scope ('Filter by city name'), and distinguishes from siblings by focusing on store listings rather than availability, products, or other operations. It provides concrete details about the dataset size (~360 stores) and geographic context (Finland).

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?

The description explicitly states when to use this tool ('Filter by city name'), providing clear context for its filtering capability. However, it doesn't mention when NOT to use it or name specific alternatives among the sibling tools (e.g., get_store_hours for hours information), leaving some room for improvement in distinguishing from closely related siblings.

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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