MoveMate: Gym Workout Tracker

Get body profile

get_body_profile

Read-only

Body stats and training preferences the user entered in MoveMate (height, weight, age, gender, fitness level, activity level, goals, available equipment), whether MoveMate onboarding is complete, and the lifetime count of completed workouts. Use for program design or nutrition estimates that depend on these values.

Input Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

Output Schema

TableJSON Schema

Name	Required	Description	Default
`age`	Yes
`goals`	Yes
`gender`	Yes
`height_cm`	Yes
`weight_kg`	Yes
`fitness_level`	Yes
`activity_level`	Yes
`available_equipment`	Yes
`onboarding_complete`	Yes
`lifetime_completed_workouts`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

Changed2 schema fields changedOct 3, 2026

removedOutput schema / properties / injuries_or_limitations

Removed value: -{
-  "items": {
-    "type": "string"
-  },
-  "type": "array"
-}

changedOutput schema / required

Previous value: -[
-  "onboarding_complete",
-  "height_cm",
-  "weight_kg",
-  "gender",
-  "age",
-  "fitness_level",
-  "activity_level",
-  "goals",
-  "available_equipment",
-  "injuries_or_limitations",
-  "lifetime_completed_workouts"
-]New value: +[
+  "onboarding_complete",
+  "height_cm",
+  "weight_kg",
+  "gender",
+  "age",
+  "fitness_level",
+  "activity_level",
+  "goals",
+  "available_equipment",
+  "lifetime_completed_workouts"
+]

First observedOct 1, 2026

TDQS

A3.9/5.0

Behavior3/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false, and openWorldHint=false, so the safety profile is covered. The description adds that the data was 'entered in MoveMate' and includes onboarding and lifetime workout count, but much of this is likely restated from the output schema rather than adding new behavioral context.

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 two tight sentences: the first front-loads what the tool returns, and the second states the intended use. No filler or redundancy.

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?

An output schema exists, so the description need not explain return values, and annotations cover safety. It is nearly complete, but the lack of differentiation from the sibling get_profile leaves a small ambiguity for tool selection.

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?

There are zero input parameters, so there is no parameter semantics for the description to clarify. The baseline for a parameterless tool is 4.

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?

The description names a specific resource (body stats and training preferences) and enumerates its fields, so the agent knows exactly what data is returned. It does not explicitly distinguish this tool from the sibling get_profile, which is the main gap.

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 a clear use case: 'Use for program design or nutrition estimates that depend on these values.' This tells the agent when the tool is appropriate. It does not mention when not to use it or name an alternative sibling tool.

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

All MoveMate: Gym Workout Tracker tools Inspect

Try in Browser

One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

Resources

Need Help?