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snapp-mcp

by sepehr071
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Python
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Grocery categories

market_categories
Read-onlyIdempotent

Lists SnappMarket product categories and subcategories with IDs by latitude and longitude, enabling product searches using category_id or subcategory_id.

Instructions

List SnappMarket product categories and sub-categories with their ids.

The ids work as category_id / subcategory_id in market_store_products. Id 99999999 is the virtual kalabarg (government e-coupon) category.

Input Schema

NameRequiredDescriptionDefault
latYesDelivery point latitude.
longYesDelivery point longitude.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed6 schema fields changedv0.2.0
    • changedInput schema / properties / lat / description
      Previous value: -"Latitude of the delivery point (Iran: ~25 to ~40)."New value: +"Delivery point latitude."
    • removedInput schema / properties / lat / title
      Removed value: -"Lat"
    • changedInput schema / properties / long / description
      Previous value: -"Longitude of the delivery point (Iran: ~44 to ~63)."New value: +"Delivery point longitude."
    • removedInput schema / properties / long / title
      Removed value: -"Long"
    • removedInput schema / title
      Removed value: -"market_categoriesArguments"
    • changedOutput schema / (root)
      Previous value: -{
-  "additionalProperties": true,
-  "title": "market_categoriesDictOutput",
-  "type": "object"
-}New value: +null
  2. First observedv0.1.1

TDQS

A4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, openWorldHint and destructiveHint=false, so safety is covered. The description adds genuine extra context the annotations cannot: the special virtual kalabarg category id 99999999 and the downstream role of the returned ids. It says nothing about return shape or hierarchy, but with annotations carrying the behavioral profile that is a minor gap.

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?

Two short sentences with no filler: the core action first, then the integration detail and the one exceptional id. Nothing is repeated from the schema or annotations, and every sentence earns its place.

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 no output schema, the description usefully summarizes the return value (categories and sub-categories plus ids) and flags the one special id, which is the kind of thing an agent would otherwise get wrong. It stops short of clarifying whether sub-categories are nested or returned as a flat list, but it is sufficient for a two-parameter, read-only reference tool.

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%, so lat/long are already documented as the delivery point and the schema documents the numeric bounds. The description adds no parameter-level detail and does not explain why a location is required to list categories. 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?

States a specific verb and resource ('List SnappMarket product categories and sub-categories with their ids') and names the sibling that consumes the output, market_store_products. An agent can distinguish this reference-data lookup from the search/cheapest/store tools in the market_* family without opening a schema.

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 explains what to do with the output ('The ids work as category_id / subcategory_id in market_store_products'), which implies the intended workflow, but it never states when to call this tool versus alternatives such as market_search or market_stores. Usage is implied rather than explicit, and no prerequisites or exclusions are given.

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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