MyFitnessPal MCP Server

Instructions

Implementation Reference

• server.py:370-460 (handler)

  Handler function for 'get_date_range_summary' tool. Decorated with @mcp.tool for registration. Fetches daily data over date range, computes averages for calories/macros/water, tracking stats, and daily breakdown using MyFitnessPalClient.
  @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)}")