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Product Data Tools MCP Server

Product Data Tools MCP Server

by ABAKHAR721
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python

get_available_fields

Retrieve available data fields for filtering and sorting product data. Optionally specify a store name to get fields specific to that store.

Instructions

Retrieves the list of available data fields (columns) for filtering and sorting.

Queries the separate Product Data Server.

Args: store_name: Optional. The name of the store to check fields for. If omitted, returns fields available across all stores.

Returns: A dictionary containing a list of available fields (e.g., {'available_fields': [...]}), or a string error message.

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": "get_available_fields"
  }
}

Input Schema

NameRequiredDescriptionDefault
store_nameNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.4/5.0
Behavior4/5

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

With no annotations, the description carries full burden. It discloses the separate server query and return format (dictionary or error string). Could mention idempotency but adds significant value.

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?

Concise two-sentence description plus structured Args/Returns. Front-loaded with purpose. Every sentence adds value.

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 one optional parameter and no output schema, the description covers purpose, parameter semantics, return format, and server dependency. Complete for a simple retrieval tool.

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 single parameter store_name is fully described beyond the schema: optional, meaning, and default behavior. Schema coverage is 0%, so description compensates completely.

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 it retrieves available data fields for filtering and sorting, and mentions querying a separate server. It distinguishes from sibling tools that deal with products.

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 the store_name parameter behavior but lacks explicit guidance on when to use this tool versus alternatives. No exclusions or prerequisites mentioned.

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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