Trainerize MCP Server and API by Cotlet

Message client in Trainerize

trainerize_message_client

Read-onlyIdempotent

Message client 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_message_client"
  }
}

Input Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

AddedNov 9, 2026

TDQS

A3.9/5.0

Behavior4/5

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

Annotations already declare readOnlyHint=true and openWorldHint=false; the description reinforces this by saying it "opens nothing by itself," so there is no contradiction. It adds genuinely useful context beyond the annotations: the return shape (screens, buttons, fields) and the plan/add-on restriction on Trainerize's official API.

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?

The workflow and the no-side-effects guarantee are front-loaded, which is good. But "from ChatGPT, Claude or any AI agent" is marketing filler, and the long parenthetical API-plan caveat with a dated "(checked 10 Oct 2026)" stamp adds bulk that could be trimmed to one short clause.

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 parameters and no output schema, the description carries the burden of explaining what comes back, and it does so (step-by-step screens/buttons/fields). The only gap is that it doesn't say whether the returned instructions are static generic guidance or account-specific, which matters for how the agent should apply them.

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 tool takes zero parameters, so there is nothing for the description to disambiguate; baseline for a parameterless tool is 4. The description does not waste words restating schema content, which is appropriate here.

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?

States a specific verb and resource ("Message client ... in the user's own Trainerize account") and clarifies the surprising part of the contract: it "Returns how to do it in Trainerize step by step (screens, buttons, fields) and opens nothing by itself." That distinguishes it from action-performing siblings, though it never names a specific sibling tool to contrast 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?

Gives a clear two-step workflow: call this to get instructions, then execute with the cotlet_browser_* tools in the user's Trainerize Cloud Browser. The API-plan note implicitly explains why this route is used instead of an API call, but there is no explicit "do not use this if..." exclusion.

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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