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preview_workout_payload

Preview a Garmin workout payload to verify structure and content before submission. Supports strength training and other workout types.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
workout_dataYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • The MCP tool handler for 'preview_workout_payload'. Decorated with @mcp.tool, it takes workout_data dict and returns the built payload using the helper build_workout_payload.
    @mcp.tool
    def preview_workout_payload(workout_data: dict) -> dict:
        return {"payload": build_workout_payload(workout_data)}
  • The core helper function that builds the Garmin API workout payload from validated input. It validates input, maps sport types, processes steps, and constructs the full payload dict.
    def build_workout_payload(workout: dict[str, Any]) -> dict[str, Any]:
        parsed = validate_workout_input(workout)
        sport_type_key = parsed.type.lower()
        sport_type = _get_sport_type(sport_type_key)
        steps, next_order = _process_steps(parsed.steps, sport_type_key, 1)
        payload = {
            "sportType": sport_type,
            "subSportType": None,
            "workoutName": parsed.name,
            "description": parsed.description,
            "estimatedDistanceUnit": {"unitKey": None},
            "workoutSegments": [
                {
                    "segmentOrder": 1,
                    "sportType": sport_type,
                    "workoutSteps": steps,
                }
            ],
            "avgTrainingSpeed": None,
            "estimatedDurationInSecs": _estimate_duration(steps),
            "estimatedDistanceInMeters": _estimate_distance(steps),
            "estimateType": None,
        }
        if next_order <= 1:
            raise ValueError("Workout must contain at least one step")
        return payload
  • Pydantic schema for workout input validation, used by validate_workout_input which is called inside build_workout_payload.
    class WorkoutInput(BaseModel):
        model_config = ConfigDict(extra="forbid")
    
        name: str = Field(min_length=1)
        type: str
        description: str | None = None
        steps: list[StepInput] = Field(min_length=1)
  • Tool is registered with FastMCP via the @mcp.tool decorator on line 114. The import of build_workout_payload from .payloads is on line 14.
    @mcp.tool
    def preview_workout_payload(workout_data: dict) -> dict:
        return {"payload": build_workout_payload(workout_data)}
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