Daily Calorie Tracker MCP Server
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Daily Calorie Tracker MCP ServerLog dinner: grilled salmon with asparagus and brown rice"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Daily Calorie Tracker MCP Server
A Model Context Protocol (MCP) server for tracking daily calorie consumption through natural language interactions.
Features
Natural Language Meal Entry: Log meals using descriptions like "chicken salad and a glass of milk"
Daily Summaries: Get total calorie intake with meal breakdowns
Weekly Reports: View average consumption, trends, and achievement tracking
Food Search: Look up calorie information for specific foods
Persistent Storage: SQLite database for cross-session data retention
Related MCP server: Food Tracker MCP Server
Installation
Via npm (Recommended)
npm install -g daily-calorie-tracker-mcpFrom Source
Clone this repository
Install dependencies:
npm installBuild the project:
npm run build
MCP Server Configuration
For Claude Desktop
Add to your Claude Desktop configuration file:
MacOS: ~/Library/Application Support/Claude/claude_desktop_config.json
Windows: %APPDATA%\Claude\claude_desktop_config.json
NPM Installation Configuration:
{
"mcpServers": {
"daily-calorie-tracker": {
"command": "npx",
"args": ["-y", "daily-calorie-tracker-mcp"]
}
}
}Local Installation Configuration:
{
"mcpServers": {
"daily-calorie-tracker": {
"command": "node",
"args": ["/path/to/daily-calorie-tracker/dist/index.js"]
}
}
}For Cursor
Add to your Cursor settings (~/.cursor/settings.json):
{
"mcpServers": {
"daily-calorie-tracker": {
"command": "npx",
"args": ["-y", "daily-calorie-tracker-mcp"]
}
}
}For Continue.dev
Add to your Continue configuration (~/.continue/config.json):
{
"models": [
{
"model": "claude-3-5-sonnet-latest",
"provider": "anthropic",
"mcpServers": [
{
"name": "daily-calorie-tracker",
"command": "npx",
"args": ["-y", "daily-calorie-tracker-mcp"]
}
]
}
]
}Available MCP Tools
The server provides the following tools:
add_meal
Log a meal with natural language description.
Parameters:
description(string, required): Natural language description of the meal (e.g., "chicken salad and a glass of milk")mealType(string, required): Type of meal - "breakfast", "lunch", "dinner", or "snack"
Example:
Add breakfast: oatmeal with banana and coffeeget_daily_summary
Get today's calorie intake summary with meal breakdown.
Parameters:
date(string, optional): Date in YYYY-MM-DD format (defaults to today)
Example:
Show today's calorie summaryget_weekly_report
Generate a weekly calorie consumption report with statistics.
Parameters:
startDate(string, optional): Start date in YYYY-MM-DD format (defaults to 7 days ago)
Example:
Generate weekly reportsearch_food
Search for calorie information of specific foods.
Parameters:
foodName(string, required): Name of the food to search
Example:
Search calories for pizzaUsage Examples
Once configured, you can use natural language to track your calories:
"Log breakfast: oatmeal with banana and coffee"
"Add lunch: grilled chicken salad and apple juice"
"Record dinner: pasta with tomato sauce and a glass of wine"
"I had a snack: apple and yogurt"
"Show today's calorie summary"
"What did I eat today?"
"Generate weekly report"
"Show my calorie trends for this week"
"Search calories for pizza"
"How many calories in chicken breast?"
Data Storage
Data is stored in SQLite database at:
MacOS/Linux:
~/.daily-calorie-tracker/calories.dbWindows:
%USERPROFILE%\.daily-calorie-tracker\calories.db
Food Database
The server includes a comprehensive food database with 100+ common foods organized by categories:
Proteins (chicken, beef, fish, eggs, tofu, etc.)
Carbohydrates (rice, pasta, bread, potatoes, etc.)
Vegetables (broccoli, spinach, tomatoes, etc.)
Fruits (apples, bananas, berries, etc.)
Beverages (milk, juice, coffee, tea, etc.)
Dairy products (cheese, yogurt, butter, etc.)
Common meals (hamburger, pizza, sandwiches, etc.)
Snacks (chips, nuts, chocolate, etc.)
Development
npm run dev- Run in development modenpm run build- Build for productionnpm start- Run production build
Contributing
Contributions are welcome! Please feel free to submit a Pull Request.
License
MIT License - see LICENSE file for details
Repository
This server cannot be deployed
Maintenance
Related MCP Connectors
Food logging, nutrition summaries, and meal photo calorie and macro estimates.
Natural-language calorie lookup. Send '2 large eggs', get USDA-sourced nutrition data.
Log meals, check calories and macros, set up a nutrition plan, and search foods.
AI-powered calorie tracking with photo recognition, barcode scanning, and voice logging
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