Garden Design MCP Server

get_categories

Retrieve product categories for a chosen garden layer and use the IDs to filter products; for plants, fetch subcategories to obtain leaf IDs for accurate filtering.

Instructions

Get product categories for a layer. Architecture and ground are flat (1-level): any returned id works directly with search_products.categoryId. Plants use a 2-level tree: this returns only the 6 top-level groups (Drzewa, Krzewy, Pnącza, Byliny, Trawy Ozdobne, Pokroje); to filter search_products by plant category you must follow up with get_subcategories() and pass a leaf id.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "layer": "<layer>"
    },
    "name": "get_categories"
  }
}

Input Schema

Name	Required	Description	Default
`layer`	Yes	Product layer

Schema Changelog

Changes observed during successful MCP inspections.

First observedv2.9.3Nov 6, 2026

TDQS

A4.6/5.0

Behavior4/5

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

No annotations exist, so the description carries the full burden, and it does disclose a non-obvious behavioral trait: the plants layer returns only 6 top-level groups that cannot be used as search filters. It stops short of covering edge cases such as empty results, error behavior, or whether the list is static or cacheable.

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?

Two sentences, front-loaded with the action and result shape, then the branch-specific caveat. The parenthetical enumeration of the six Polish group names is somewhat heavy but earns its place by letting the agent verify it is looking at top-level groups.

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?

For a one-parameter read tool with no output schema, the description supplies everything needed: what is returned, how the shape varies by layer, and the mandatory follow-up path for plants. Nothing an agent needs in order 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.

Parameters4/5

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

Schema coverage is 100% with an enum, so the baseline would be 3, but the description adds real meaning the enum cannot: what each layer value implies about tree depth and downstream usability of returned ids. It gives behavioral semantics per enum value rather than restating the parameter.

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 product categories for a layer') and immediately characterizes the result shape per layer value, so an agent knows exactly what comes back and how it differs from the sibling get_subcategories.

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?

It states explicitly that architecture/ground ids work directly with search_products.categoryId, while plants requires a follow-up call to get_subcategories(<top-level id>) and a leaf id. The alternative and the condition that selects it are both named, with no inference required.

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

Deploy Server