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baneh-mcp

baneh-mcp

by sepehr071
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

List brands

bn_brands
Read-onlyIdempotent

List brands with slugs and product counts, sorted by product count, and filter by name or slug. Use returned slugs to browse products by brand.

Instructions

List brands (about 150, e.g. LG, Samsung, Bosch, Xiaomi) with slug and product count, biggest first.

Slug goes to bn_browse's brand. Counts include out-of-stock products; not every product has a brand.

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": "bn_brands"
  }
}

Input Schema

NameRequiredDescriptionDefault
limitNoMax brands.
queryNoName or slug contains this, e.g. 'bosch'.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changedv0.2.0
    • changedInput schema / properties / limit / description
      Previous value: -"Max brands to return."New value: +"Max brands."
    • changedInput schema / properties / query / description
      Previous value: -"Only brands whose name or slug contains this, e.g. 'سامسونگ' or 'bosch'."New value: +"Name or slug contains this, e.g. 'bosch'."
  2. First observedv0.1.0

TDQS

A4/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, openWorld and non-destructive, so the safety profile is covered. The description adds genuinely useful behavior the annotations cannot convey: the ordering ('biggest first'), the data caveat that counts include out-of-stock products, and that not every product has a brand. It omits anything about how `limit` truncates results or whether a total is returned, which keeps it below 5.

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, zero filler, with the scale, return shape and ordering front-loaded and the data caveats trailing. Every clause carries distinct information an agent needs.

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 still names the returned fields, the sort order, and two data caveats, which is nearly everything needed to call it correctly. The remaining gap is pagination/truncation behavior given the max-100 `limit`, which is left implicit.

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%, with both `limit` and `query` fully documented in the schema, so the baseline is 3. The description adds ordering context ('biggest first') that explains what the returned list is sorted by, but says nothing about `query` matching or what happens when `limit` is hit beyond the schema's own text.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description gives a specific verb and resource ('List brands'), plus concrete scale ('about 150'), examples (LG, Samsung, Bosch, Xiaomi), return fields ('slug and product count') and ordering ('biggest first'). That is far more than a restatement of the title. It stops short of explicitly distinguishing itself from the sibling bn_categories, which an agent browsing this family could plausibly confuse it with.

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?

It clearly routes the agent downstream: 'Slug goes to bn_browse's `brand`', which tells the caller exactly why and how to use the result. There are no exclusions or when-not guidance relative to bn_categories or bn_search, and the `query` filtering path is never framed as a use case, so it falls short of a 5.

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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