cyclesite-mcp-server

list_brands

Read-onlyIdempotent

Paginated UK bike-brand catalogue from Cyclesite, ordered by stock level. Use to validate a brand name, surface options to a user, or paginate 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

TableJSON Schema

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

Output Schema

TableJSON Schema

Name	Required	Description
`limit`	No
`total`	No
`brands`	No
`offset`	No
`hasMore`	No
`attribution`	No	Citation string — include verbatim when surfacing data.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

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

A4.5/5.0

Behavior5/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint. The description adds beyond that by disclosing that stock counts are returned as bands (none / 1-5 / 6-25 / 26-100 / 100+) due to Cyclesite not exposing precise inventory, and that results are ordered by stock level. This is valuable behavioral context not present in the annotations.

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?

The description is three compact sentences that front-load the core purpose, then provide usage guidance, and finally disclose the stock-band limitation. Every sentence adds value with no redundancy.

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 the tool's simplicity, the existence of an output schema, and the annotations, the description covers purpose, usage, and a key behavioral limitation. It is complete for an agent to select and invoke the tool correctly.

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?

The input schema already fully documents q, limit, and offset with descriptions (100% coverage), so the baseline is 3. The description adds general context about pagination and ordering but doesn't add new parameter-specific semantics beyond the schema.

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 the tool lists a paginated catalogue of UK bike brands from Cyclesite, ordered by stock level, and distinguishes it from sibling tools like list_models_for_brand by focusing on brands. It also gives concrete use cases (validate a brand name, surface options, paginate). This is a specific verb+resource+scope statement.

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?

The description explicitly says when to use it: to validate a brand name, surface options to a user, or paginate the catalogue. It doesn't name alternatives or exclusions, but the context is clear enough for an agent to select it over related tools like list_models_for_brand.

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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