cyclesite-mcp-server

List brands

list_brands

Read-onlyIdempotent

Paginated UK bike-brand catalogue from Cyclesite, ordered by stock level, for checking a brand name, listing the options or paging through the catalogue. Stock counts are returned as bands (none / 1-5 / 6-25 / 26-100 / 100+); Cyclesite doesn't expose precise per-brand inventory. Example: 'what brands of e-bike are available?'.

Input Schema

Name	Required	Description
`q`	No	Optional search filter (case-insensitive contains).
`limit`	No	1-50, default 25.
`offset`	No	0-500.

Output Schema

Name	Required	Description
`limit`	No
`total`	No
`brands`	No
`offset`	No
`hasMore`	No
`attribution`	No	Citation string for the data in this result.

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedNov 3, 2026

changedOutput schema / properties / attribution / description

Previous value: -"Citation string — include verbatim when surfacing data."New value: +"Citation string for the data in this result."

Changed1 schema field changedJul 15, 2026
- changedOutput schema / properties / brands / items / properties / country / type
```
Previous value: -"string"New value: +[
+  "string",
+  "null"
+]
```
First observedMay 7, 2026

TDQS

A4.1/5.0

Behavior4/5

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

Annotations already declare readOnly/idempotent/non-destructive, so the safety profile is covered. The description adds genuinely new behavior: results are ordered by stock level and inventory is only exposed as coarse bands (none / 1-5 / 6-25 / 26-100 / 100+), which warns the agent not to expect precise counts.

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?

Purpose and stock-band caveat are front-loaded, and the example earns its place by showing a realistic invocation. The opening sentence is long and slightly run-on, but there is little waste.

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 an output schema present and full parameter documentation, the description only needs to frame scope and any surprising return semantics, which the stock-band explanation does. Nothing essential for a correct call is missing.

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 q/limit/offset semantics are already documented in the schema. The description only gestures at paging and name-checking, adding no syntax or format detail beyond the schema; baseline 3 applies.

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?

States a specific verb and resource ('Paginated UK bike-brand catalogue from Cyclesite'), plus ordering by stock level and domain scope. That is enough to tell it apart from list_models_for_brand, which returns models within a brand rather than the brands themselves.

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?

Gives clear usage contexts (checking a brand name, listing options, paging through the catalogue) and an example question that makes the intended call obvious. It does not explicitly name a sibling as the alternative or state when not to use it.

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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