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masterkala-mcp

by sepehr071
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

Product details

mk_product
Read-only

Fetch a single product's full record by ID: price and discount in Toman, stock status and count, buyable colors, brand, category path, rating, and branches.

Instructions

Get one product's full record: price and discount (Toman), stock status and count, colors and which are buyable, brand, category path, rating, and the physical branches that have it.

Use after mk_search / mk_browse when the user picks a product. Specs table: mk_specs. Reviews: mk_reviews. Delivery date and fee: mk_shipping.

Input Schema

NameRequiredDescriptionDefault
full_textNoReturn the description uncut (default cuts at 300 chars).
product_idYesMasterKala product id from mk_search / mk_browse, e.g. 24855.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed4 schema fields changedv0.3.0
    • addedInput schema / properties / full_text
      Added value: +{
+  "default": false,
+  "description": "Return the description uncut (default cuts at 300 chars).",
+  "type": "boolean"
+}
    • removedInput schema / properties / product_id / title
      Removed value: -"Product Id"
    • removedInput schema / title
      Removed value: -"mk_productArguments"
    • changedOutput schema / (root)
      Previous value: -{
-  "additionalProperties": true,
-  "title": "mk_productDictOutput",
-  "type": "object"
-}New value: +null
  2. First observedv0.1.0

TDQS

A4.3/5.0
Behavior4/5

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

The annotations only provide readOnlyHint=true, so the description must carry most behavioral weight. It discloses the rich payload structure (price/discount in Toman, stock status/count, colors and buyable status, brand, category path, rating, physical branches) and the default truncation of product descriptions at 300 chars, but doesn't mention pagination, rate limits, or error conditions.

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?

Front-loaded with the core action and payload summary, then two efficient sentences for usage and cross-references. The 300-char truncation detail in the schema is complemented by 'Return the description uncut' in the description, keeping the body tight without redundancy.

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 single-record fetch tool with two simple parameters and full schema coverage, the description covers purpose, usage routing, and returned data structure. It would benefit from a note on behavior when product_id is invalid, but overall it is sufficient.

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 the schema already documents both parameters (product_id and full_text). The description adds no parameter-level details beyond the schema, which matches the baseline 3 for full coverage.

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 one product's full record') and then enumerates the returned fields, leaving no ambiguity about what the tool does. This is clearly distinct from siblings like mk_search (search) and mk_specs (specifications).

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

Usage Guidelines5/5

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

The description explicitly states when to use it ('Use after mk_search / mk_browse when the user picks a product') and routes three related concerns to their proper tools (mk_specs, mk_reviews, mk_shipping). This is textbook usage guidance.

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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