How to Integrate Retool with MyFitnessPal

MyFitnessPal allows users to export their food diary history from the web application. The export is not available in the mobile app — users must log into myfitnesspal.com on a desktop browser. Once logged in, navigate to Reports in the top navigation bar. Click the export icon or navigate to Settings → Diary Settings → Export Data. MyFitnessPal generates a CSV file containing all logged food entries with columns including: Date, Meal, Food Name, Calories, Carbohydrates (g), Fat (g), Protein (g), Sodium (mg), Sugar (g), and optionally Fiber (g) and Saturated Fat (g) depending on the foods logged. Download this CSV file. Before importing into Retool, clean the data: open the CSV in a spreadsheet editor and check for blank rows (which appear when a daily diary entry has no logged foods), rows with 'Totals' labels (which MyFitnessPal inserts as daily summary rows), and any special characters in food names that may interfere with SQL INSERT statements. Remove 'Totals' rows and ensure the Date column uses a consistent format (YYYY-MM-DD or MM/DD/YYYY). If handling multiple clients or users, add a client_id or user_email column to identify whose data each row belongs to. Save the cleaned CSV. For ongoing programs, establish a weekly export schedule where participants download and submit their CSV files — a simple file upload form can be built in Retool to receive these submissions.

With a cleaned CSV ready, create the target database table and import the data. If using Retool Database (the built-in managed PostgreSQL), navigate to the Retool Database tab in the left sidebar, click Create Table, and name it 'nutrition_log'. Define these columns: id (auto-increment primary key), user_email (text), entry_date (date), meal_type (text), food_name (text), calories (integer), carbohydrates_g (decimal), fat_g (decimal), protein_g (decimal), sodium_mg (decimal), sugar_g (decimal), fiber_g (decimal), imported_at (timestamp, default now()). Click the Import CSV button in the Retool Database interface and upload your cleaned MyFitnessPal CSV. Map each CSV column to the corresponding table column in the import dialog. For ongoing data collection, create a second table named 'nutrition_clients' with columns: id, name, email, program_start_date, calorie_target, protein_target_g, notes. This clients table lets you reference targets when flagging non-adherent days. If using an existing PostgreSQL connection, write and run the CREATE TABLE statement in Retool's SQL query editor against your PostgreSQL resource, then use Retool's table CSV import feature or a Python script to load the data. After import, run a verification query: SELECT COUNT(*), MIN(entry_date), MAX(entry_date) FROM nutrition_log to confirm all rows loaded correctly.

1-- Create the nutrition_log table (run in Retool's SQL editor)
2CREATE TABLE IF NOT EXISTS nutrition_log (
3  id SERIAL PRIMARY KEY,
4  user_email TEXT NOT NULL,
5  entry_date DATE NOT NULL,
6  meal_type TEXT,
7  food_name TEXT,
8  calories INTEGER DEFAULT 0,
9  carbohydrates_g DECIMAL(8,2) DEFAULT 0,
10  fat_g DECIMAL(8,2) DEFAULT 0,
11  protein_g DECIMAL(8,2) DEFAULT 0,
12  sodium_mg DECIMAL(8,2) DEFAULT 0,
13  sugar_g DECIMAL(8,2) DEFAULT 0,
14  fiber_g DECIMAL(8,2) DEFAULT 0,
15  imported_at TIMESTAMP DEFAULT NOW()
16);
17
18-- Verify import
19SELECT
20  user_email,
21  COUNT(*) AS total_entries,
22  MIN(entry_date) AS earliest_entry,
23  MAX(entry_date) AS latest_entry
24FROM nutrition_log
25GROUP BY user_email
26ORDER BY total_entries DESC;

For organizations that need active food nutrition lookups rather than relying solely on imported exports, configure the Nutritionix API as a second Retool Resource alongside the database resource. First, sign up for a free developer account at developer.nutritionix.com — the free tier provides 500 natural language queries per day and access to the branded food database. Once registered, note your App ID and App Key from the developer portal dashboard. In Retool Resources, click Add Resource and select REST API. Name it 'Nutritionix API'. Set Base URL to https://trackapi.nutritionix.com/v2. Under Authentication, select Header Auth. Add two headers: x-app-id with value {{ retoolContext.configVars.NUTRITIONIX_APP_ID }} and x-app-key with value {{ retoolContext.configVars.NUTRITIONIX_APP_KEY }}. Also add Content-Type: application/json as a default header. Store your App ID and App Key in Retool Configuration Variables (Settings → Configuration Variables) named NUTRITIONIX_APP_ID and NUTRITIONIX_APP_KEY, with the App Key marked as a secret. Click Save and test by creating a test query: POST to /natural/nutrients with body { 'query': '1 large egg' } — a successful response returns a foods array with macro breakdowns confirming the integration works.

1{
2  "method": "POST",
3  "path": "/natural/nutrients",
4  "body": {
5    "query": "{{ foodSearchInput.value }}"
6  },
7  "headers": {
8    "x-app-id": "{{ retoolContext.configVars.NUTRITIONIX_APP_ID }}",
9    "x-app-key": "{{ retoolContext.configVars.NUTRITIONIX_APP_KEY }}"
10  }
11}

With both the database resource (for imported diary data) and optionally the Nutritionix resource (for food lookup) configured, build the main dashboard. Start with a Select component named 'clientSelect' that populates from a query against the nutrition_clients table: SELECT id, name, email FROM nutrition_clients ORDER BY name. Add a Date Range Picker named 'dateRange' for filtering the analysis period, defaulting to the last 30 days. Create the core analytics query 'getDailyTotals': SELECT entry_date, SUM(calories) as total_calories, SUM(protein_g) as protein, SUM(carbohydrates_g) as carbs, SUM(fat_g) as fat FROM nutrition_log WHERE user_email = {{ clientSelect.value }} AND entry_date BETWEEN {{ dateRange.start }} AND {{ dateRange.end }} GROUP BY entry_date ORDER BY entry_date. Bind this query's data to a Line Chart showing daily calorie trend over the selected period, with a reference line at the client's calorie target. Below the chart, add three Stat components showing average daily calories, average protein, and average adherence rate (percentage of days within 10% of calorie target). Add a second Table below showing the daily totals with color-coded Tags for days that are 'On Track', 'Under Target', or 'Over Target' based on comparison to the client's goal. For the Nutritionix food lookup panel, add a Text Input and Search Button that trigger the Nutritionix query and display results in a detail Card with a breakdown of macros and a 'Add to Meal Plan' button.

1-- Daily nutrition totals query for selected client and date range
2SELECT
3  entry_date,
4  SUM(calories) AS total_calories,
5  ROUND(SUM(protein_g)::numeric, 1) AS protein_g,
6  ROUND(SUM(carbohydrates_g)::numeric, 1) AS carbs_g,
7  ROUND(SUM(fat_g)::numeric, 1) AS fat_g,
8  ROUND(SUM(sodium_mg)::numeric, 1) AS sodium_mg,
9  COUNT(DISTINCT meal_type) AS meals_logged
10FROM nutrition_log
11WHERE user_email = {{ clientSelect.value }}
12  AND entry_date BETWEEN {{ dateRange.start }}::date
13  AND {{ dateRange.end }}::date
14GROUP BY entry_date
15ORDER BY entry_date;

To make the dashboard a complete health coaching tool, add coaching workflow features. Create a 'coaching_notes' table in the connected database with columns: id, client_email, note_date, note_text, coach_name, created_at. In the Retool dashboard, add a Notes section below the nutrition charts with a Text Area input, a Text Input for the coach's name, and a Save Note button that runs an INSERT query. Display existing notes in a small Table sorted by note_date descending, allowing coaches to track the history of their observations per client. Add a Report generation feature: a Button labeled 'Generate Weekly Summary' that triggers a JavaScript query computing key metrics for the current week (total calories, avg protein, best and worst adherence days, streak of consecutive logging days), formats them into a text summary, and copies it to the clipboard for pasting into emails. Finally, add a macro balance pie chart using a Chart component in Donut mode, with data computed from the getDailyTotals averages: protein calories (protein_g × 4), carb calories (carbs_g × 4), and fat calories (fat_g × 9), showing the macronutrient distribution as percentages. For complex integrations involving multi-coach access control, automated weekly report emails, and integration with clinical EMR systems, RapidDev's team can help architect and build your Retool nutrition management solution.

1// JavaScript transformer: compute macro balance percentages for Pie Chart
2const totals = getDailyTotals.data || [];
3if (!totals.length) return [];
4
5const avgProtein = totals.reduce((s, d) => s + (d.protein_g || 0), 0) / totals.length;
6const avgCarbs = totals.reduce((s, d) => s + (d.carbs_g || 0), 0) / totals.length;
7const avgFat = totals.reduce((s, d) => s + (d.fat_g || 0), 0) / totals.length;
8
9const proteinCal = avgProtein * 4;
10const carbCal = avgCarbs * 4;
11const fatCal = avgFat * 9;
12const total = proteinCal + carbCal + fatCal;
13
14return [
15  { macro: 'Protein', calories: Math.round(proteinCal), pct: ((proteinCal / total) * 100).toFixed(1) },
16  { macro: 'Carbohydrates', calories: Math.round(carbCal), pct: ((carbCal / total) * 100).toFixed(1) },
17  { macro: 'Fat', calories: Math.round(fatCal), pct: ((fatCal / total) * 100).toFixed(1) }
18];