Trainerize MCP Server and API by Cotlet

List clients in Trainerize

trainerize_list_clients

Read-onlyIdempotent

List clients in the user's own Trainerize account from ChatGPT, Claude or any AI agent. Returns how to do it in Trainerize step by step (screens, buttons, fields) and opens nothing by itself; then do it with the cotlet_browser_* tools in the user's Trainerize Cloud Browser. Trainerize's official API: Trainerize has an API, but only on Studio and Enterprise plans or with the paid FitMetrics add-on (checked 10 Oct 2026).

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": "trainerize_list_clients"
  }
}

Input Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

AddedNov 9, 2026

TDQS

A3.7/5.0

Behavior4/5

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

Annotations already declare readOnly/idempotent/non-destructive, and the description adds genuinely useful behavior beyond them: the tool performs no action itself and returns instructional content, and it notes the official API is gated to Studio/Enterprise or the paid FitMetrics add-on. It does not describe the shape of the returned guide (length, sections), which keeps it from a 5.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three sentences, with the critical clarification ('returns how to do it... opens nothing by itself') placed after a sentence that implies direct listing. The platform enumeration ('from ChatGPT, Claude or any AI agent') and the dated API-plan aside are filler that dilutes the front-loaded message.

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?

For a zero-parameter guide tool with no output schema, it covers what is returned (step-by-step screens/buttons/fields), that no action is taken, and what to do next. It leaves the return format and any failure/fallback behavior unspecified, a modest gap.

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?

The schema has zero parameters and 100% coverage, so there is nothing to disambiguate. The description adds no parameter detail and none is needed.

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

Purpose3/5

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

The name and title say 'List clients', and the first sentence repeats that, but the second sentence reveals the tool actually returns a step-by-step guide ('screens, buttons, fields') and 'opens nothing by itself.' The agent gets the real behavior only after reading past a misleading opening, so the verb/resource statement is internally in tension rather than cleanly specific.

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 gives clear workflow context: call this to get the steps, then execute them with the cotlet_browser_* tools in the Trainerize Cloud Browser. It does not name when to prefer a sibling (e.g., cotlet_app_guide) or when not to use this, so it stops short of full routing guidance.

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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