letu-mcp

compare_products

Read-onlyIdempotent

Compare up to 10 L'Etoile products side-by-side: each product's price, club-card discount, rating, delivery, seller, and available variants in one view.

Instructions

Side-by-side rows for up to 10 products, one variant each.

Per product: the pinned variant, or the cheapest one (orderable in the city when with_delivery), its site price and price without the club card, list price, rating (all variants) and counts, seller, delivery in the city, the card's price range and number of variants. Takes ~3–5 requests per product (~2 s each).

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "products": "<products>"
    },
    "name": "compare_products"
  }
}

Input Schema

Name	Required	Description
`city`	No	City name as on letu.ru (e.g. 'Екатеринбург', 'Москва'). Default: LETU_CITY, else the city letu.ru assigns to this IP. Prices do not depend on the city; delivery, store stock and the variants available do.
`products`	Yes	Up to 10 product ids / URLs; 'productId:skuId' pins a variant
`with_delivery`	No	Check that the compared variant is orderable in the city (and pick the cheapest one that is)

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Sep 25, 2026

TDQS

A3.9/5.0

Behavior4/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint. The description adds valuable behavioral details: the variant selection logic (pinned or cheapest orderable when with_delivery) and performance characteristics (~3–5 requests per product, ~2 s each). This goes beyond the structured hints and does not contradict them.

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?

The description is front-loaded with the main purpose, followed by a compact list of per-product details and a performance note. It is efficient with no fluff, though the second paragraph is a dense list that could be slightly streamlined without losing value.

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?

With an output schema present, return values are covered. The description explains the variant selection, the data fields shown, and performance, which is sufficient for an agent to call the tool correctly. Minor gaps like error handling are not essential given the annotations and schema.

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% — each parameter already has a detailed description. The tool description does not add new meaning beyond the schema; it reiterates the variant selection and city influence, which are already present in the schema descriptions. Baseline 3 applies.

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 first line 'Side-by-side rows for up to 10 products, one variant each' uses a specific verb (compare) and resource (products), and the focus on multiple products clearly distinguishes it from siblings like get_product (single product) and search_products (search).

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?

The description implies usage for comparing multiple products, but does not explicitly state when to use this tool versus alternatives. No exclusions or alternative routing are provided, though the context is clear enough for an agent to infer the appropriate scenario.

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

Deploy Server