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wildberries-mcp-ru

wb_get_stocks

Read-only

Retrieve a point-in-time Wildberries stock snapshot with quantity, warehouseName, and nmId; set date_from to fetch all current stock rows.

Instructions

Get the current Wildberries stock snapshot (Statistics API, 1 req/min).

Stocks have no history — this is a point-in-time snapshot. Use an early date_from to get the full current set.

Args: date_from: RFC3339 date; default "2020-01-01" returns everything in stock now. Returns JSON: {"ok": true, "data": [ stock rows ]} with quantity, warehouseName, nmId.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
date_fromNo2020-01-01

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.5.3

TDQS

A4.8/5.0
Behavior5/5

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

Annotations already mark readOnlyHint and openWorldHint, but the description adds valuable behavioral context beyond those: it explicitly states the rate limit (1 req/min), clarifies that stocks are a point-in-time snapshot with no history, and describes the return envelope. This is rich, non-contradictory detail that helps the agent set expectations.

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 compact and well-structured: a one-line purpose, a note on snapshot semantics, then Args and Returns sections. It front-loads the core purpose and rate limit, and every sentence adds value—no filler or redundancy.

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?

Given the tool's simplicity (one optional parameter, no required fields) and that an output schema exists, the description covers all essential operational aspects: purpose, rate limit, parameter semantics, and return format. Nothing an agent needs to call it correctly is missing.

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

Parameters5/5

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

The schema only declares a default value with zero description coverage, so the description fully compensates. It explains the parameter format (RFC3339 date), its default, and its effect ('returns everything in stock now'). This gives the agent clear, actionable meaning beyond the bare schema.

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 opens with a specific verb and resource: 'Get the current Wildberries stock snapshot.' It clearly identifies the platform (Wildberries) and the data (stock). While it doesn't name sibling tools, the resource is unambiguous and the tool name aligns, so an agent can easily distinguish it from tools like wb_get_sales or wb_get_prices.

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 provides a concrete usage hint: 'Use an early date_from to get the full current set.' This guides parameter selection effectively. However, it does not explicitly state when to use this tool over alternatives (e.g., avito_get_stocks or ozon_get_stocks), though the platform is implied by the name. The hint is useful but not a full when/when-not breakdown.

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