MyFitnessPal MCP Server

Instructions

Implementation Reference

• server.py:370-460 (handler)

  The handler function for the 'get_date_range_summary' tool. It fetches daily nutrition data over a date range using the MyFitnessPal client, computes averages and statistics, and returns a formatted markdown summary including daily averages, tracking stats, and a daily breakdown.

  @mcp.tool
  def get_date_range_summary(start_date: str, end_date: str):
      """
      Get aggregate nutrition data over a date range with trends and insights.
      
      Args:
          start_date: Start date in YYYY-MM-DD format
          end_date: End date in YYYY-MM-DD format
      """
      try:
          start = parse_date(start_date)
          end = parse_date(end_date)
          
          if start > end:
              raise ValueError("Start date must be before or equal to end date")
          
          client = get_client()
          
          # Collect data for each day
          daily_data = []
          
          for day in client.get_date_range(start, end):
              totals = day.totals
              
              daily_data.append({
                  'date': day.date,
                  'calories': totals.get('calories', 0),
                  'carbs': totals.get('carbohydrates', 0),
                  'fat': totals.get('fat', 0),
                  'protein': totals.get('protein', 0),
                  'water_ml': day.water,  # Store as ml
                  'complete': day.complete,
                  'num_meals': len(day.meals),
                  'num_exercises': len(day.exercises)
              })
          
          if not daily_data:
              return text_response("No data available for the specified date range.")
          
          # Calculate aggregates
          num_days = len(daily_data)
          avg_calories = sum(d['calories'] for d in daily_data) / num_days
          avg_carbs = sum(d['carbs'] for d in daily_data) / num_days
          avg_fat = sum(d['fat'] for d in daily_data) / num_days
          avg_protein = sum(d['protein'] for d in daily_data) / num_days
          avg_water_ml = sum(d['water_ml'] for d in daily_data) / num_days
          avg_water_oz = avg_water_ml / 29.5735
          
          complete_days = sum(1 for d in daily_data if d['complete'])
          days_with_exercise = sum(1 for d in daily_data if d['num_exercises'] > 0)
          
          # Format output
          output = f"# Date Range Summary\n"
          output += f"**{start.strftime('%B %d, %Y')}** to **{end.strftime('%B %d, %Y')}**\n"
          output += f"({num_days} days)\n\n"
          
          output += "## Daily Averages\n"
          output += f"- **Calories**: {avg_calories:.0f} kcal/day\n"
          output += f"- **Carbohydrates**: {avg_carbs:.0f}g/day\n"
          output += f"- **Fat**: {avg_fat:.0f}g/day\n"
          output += f"- **Protein**: {avg_protein:.0f}g/day\n"
          output += f"- **Water**: {avg_water_oz:.0f} oz/day ({avg_water_ml:.0f} ml/day)\n\n"
          
          output += "## Tracking Stats\n"
          output += f"- **Days Completed**: {complete_days}/{num_days} ({complete_days/num_days*100:.0f}%)\n"
          output += f"- **Days with Exercise**: {days_with_exercise}/{num_days} ({days_with_exercise/num_days*100:.0f}%)\n\n"
          
          output += "## Daily Breakdown\n"
          for day_data in daily_data:
              d = day_data['date']
              water_oz = day_data['water_ml'] / 29.5735
              output += f"- **{d.strftime('%Y-%m-%d')}**: "
              output += f"{day_data['calories']:.0f} kcal, "
              output += f"{day_data['carbs']:.0f}C/{day_data['fat']:.0f}F/{day_data['protein']:.0f}P, "
              output += f"{water_oz:.0f} oz water"
              
              status = []
              if day_data['complete']:
                  status.append("✓")
              if day_data['num_exercises'] > 0:
                  status.append(f"{day_data['num_exercises']} exercises")
              
              if status:
                  output += f" [{', '.join(status)}]"
              
              output += "\n"
          
          return text_response(output)
          
      except Exception as e:
          return text_response(f"Error retrieving date range summary: {str(e)}")