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mealplan-mcp

mealplan-mcp

by evcraddock

Mealplan MCP

A Model Context Provider (MCP) server for meal planning and grocery list generation.

Coverage

Quick Start

# Clone the repository
git clone <repository-url>
cd mealplan-mcp

# Set up environment variable for meal plan storage
export MEALPLANPATH="/path/to/meal/plans"

# Install dependencies with uv
uv venv && source .venv/bin/activate
uv pip install -e .

# Run the server
python main.py

Related MCP server: Unofficial AnyList MCP Server

Features

  • Store and retrieve dish recipes with ingredients and instructions

  • Create detailed meal plans for specific dates and meal types

  • Manage ignored ingredients that should be excluded from grocery lists

  • Generate grocery lists for date ranges with automatic checkboxes

  • Full MCP (Model Context Provider) compatibility for AI-driven interfaces

Available Tools

Tool

Description

Example Input

create_mealplan

Creates a meal plan

{"meal_plan": {"date": "2023-05-01", "meal_type": "dinner", "title": "Italian Night", "cook": "Chef", "dishes": [...]}}

store_dish

Stores a dish recipe

{"dish_data": {"name": "Pasta", "ingredients": [...]}}

list_dishes

Lists all stored dishes

{}

list_mealplans_by_date_range

Lists meal plans within a date range

{"date_range": {"start": "2023-06-01", "end": "2023-06-07"}}

export_mealplans_to_pdf

Exports meal plans to a PDF file

{"date_range": {"start": "2023-06-01", "end": "2023-06-07"}}

add_ignored_ingredient

Adds ingredient to ignore list

{"ingredient": "salt"}

get_ignored_ingredients

Gets all ignored ingredients

{}

generate_grocery_list

Creates a grocery list markdown

{"date_range": {"start": "2023-06-01", "end": "2023-06-07"}}

Claude Desktop Setup

To use this MCP server with Claude Desktop, add the following configuration to your claude_desktop_config.json file:

macOS

# Edit the config file
open ~/Library/Application\ Support/Claude/claude_desktop_config.json

Windows

# Navigate to the config file location
%APPDATA%\Claude\claude_desktop_config.json

Configuration

Add this server configuration to your claude_desktop_config.json:

{
  "mcpServers": {
    "mealplan": {
      "command": "uv",
      "args": [
        "--directory",
        "/path/to/your/mealplan-mcp",
        "run",
        "main.py"
      ],
      "env": {
        "MEALPLANPATH": "/path/to/your/meal/plans"
      }
    }
  }
}

Important:

  • Replace /path/to/your/mealplan-mcp/main.py with the actual path to your main.py file

  • Replace /path/to/your/meal/plans with your desired meal plan storage directory

  • Restart Claude Desktop after making changes

Development Setup

Prerequisites

  • Python 3.12 or higher

  • uv (recommended for dependency management)

Installation

  1. Clone the repository:

    git clone <repository-url>
    cd mealplan-mcp
  2. Set up the environment variable for meal plan storage:

    # macOS/Linux
    export MEALPLANPATH="/path/to/meal/plans"
    
    # Windows Command Prompt
    set MEALPLANPATH=C:\path\to\meal\plans
    
    # Windows PowerShell
    $env:MEALPLANPATH = "C:\path\to\meal\plans"
  3. Set up the virtual environment:

    # Using uv (recommended)
    uv venv
    source .venv/bin/activate  # On macOS/Linux
    # .venv\Scripts\activate    # On Windows
    
    # Alternative: Using venv (built-in)
    python -m venv .venv
    source .venv/bin/activate  # On macOS/Linux
    # .venv\Scripts\activate    # On Windows
  4. Install dependencies:

    # For basic usage (recommended)
    uv pip install -e .
    
    # For development (includes testing tools)
    uv pip install -e ".[dev]"
    
    # Alternative: Using pip
    pip install -e .              # Basic usage
    pip install -e ".[dev]"       # Development

Running the Application

To start the MCP server:

python main.py

This starts the server using stdio transport, making it compatible with MCP client applications.

Testing

The project includes comprehensive testing with automatic test isolation:

# Run all tests
pytest

# Run with coverage
pytest --cov=mealplan_mcp

# Generate a coverage report
pytest --cov=mealplan_mcp --cov-report=html

# Run specific test categories
pytest tests/mealplan/          # Meal plan tests
pytest tests/dish/              # Dish service tests
pytest tests/renderers/         # Renderer tests

MCP Examples

Using the MCP CLI Tool

The MCP CLI tool allows you to interact with your server directly from the command line:

# In a separate terminal, run your server
python main.py

# In another terminal, start the MCP CLI
mcp dev main.py

Project Structure

mealplan-mcp/
├── main.py                  # Entry point and MCP server definition
├── mealplan_mcp/            # Main application package
│   ├── models/              # Pydantic data models
│   │   ├── dish.py          # Dish model with ingredients and instructions
│   │   ├── ingredient.py    # Ingredient model with validation
│   │   ├── ignored.py       # Ignored ingredients model
│   │   ├── meal_plan.py     # Meal plan model with date validation
│   │   ├── meal_type.py     # Meal type enumerations
│   │   └── nutrient.py      # Nutrient information model
│   ├── renderers/           # Markdown rendering modules
│   │   ├── grocery.py       # Grocery list markdown renderer
│   │   └── mealplan.py      # Meal plan markdown renderer
│   ├── services/            # Business logic services
│   │   ├── dish/            # Dish-related services (store, list)
│   │   ├── grocery/         # Grocery list generation services
│   │   ├── ignored/         # Ignored ingredients services
│   │   └── mealplan/        # Meal plan storage services
│   └── utils/               # Utility functions
│       ├── paths.py         # Path handling with test isolation
│       └── slugify.py       # String slugification utilities
├── tests/                   # Comprehensive test suite (113 tests)
└── docs/                    # Documentation

Contributing

  1. Fork the repository

  2. Create a feature branch: git checkout -b feature-name

  3. Commit your changes: git commit -am 'Add some feature'

  4. Push to the branch: git push origin feature-name

  5. Submit a pull request

License

This project is licensed under the MIT License - see the LICENSE file for details.

Available Tools

8 tools
add_ignored_ingredientB

Add an ingredient to the ignored ingredients list.

Args:
    ingredient: The name of the ingredient to ignore

Returns:
    A dictionary with a confirmation message

Inputs: ingredient (required).

create_mealplanB

Create a meal plan entry with the specified parameters and save it to a file.

Args:
    meal_plan: A meal plan object containing:
        - date: The date for the meal plan
        - meal_type: The type of meal (breakfast, lunch, dinner, snack)
        - title: The title of the meal
        - cook: The person who will cook the meal
        - dishes: List of dishes to be prepared

Returns:
    str: A summary of the meal plan and the path where it was saved

Inputs: meal_plan (required).

export_mealplans_to_pdfA

Export meal plans within a specified date range to a PDF file.

Args:
    date_range: Dictionary containing start and end dates in format YYYY-MM-DD
        - start: Start date (required)
        - end: End date (required)

Returns:
    JSON string containing either:
    - Success: {"ok": "path/to/generated.pdf"}
    - Error: {"error": "error_type", "message": "error_description"}

Inputs: date_range (required).

generate_grocery_listB

Generate a grocery list for a specified date range.

Args:
    date_range: Dictionary containing start and end dates in format YYYY-MM-DD
        - start: Start date (required)
        - end: End date (required)

Returns:
    Dictionary with the path to the generated grocery list

Inputs: date_range (required).

get_ignored_ingredientsA

Get the list of ignored ingredients.

Returns:
    A sorted list of ingredient names to be ignored in grocery lists

Inputs: no named parameters.

list_dishesC

List all dishes.

Returns:
    List of dish objects converted to dictionaries

Inputs: no named parameters.

list_mealplans_by_date_rangeA

List meal plans within a specified date range.

Args:
    date_range: Dictionary containing start and end dates in format YYYY-MM-DD
        - start: Start date (required)
        - end: End date (required)

Returns:
    JSON string containing array of meal plan objects with:
    - title: Meal title (cleaned)
    - date: Date in YYYY-MM-DD format
    - meal_type: Type of meal (breakfast, lunch, dinner, snack)
    - cook: Person cooking the meal
    - dishes: Array of dish names

Inputs: date_range (required).

store_dishC

Store a dish and return a confirmation.

Args:
    dish_data: Dictionary containing dish data

Returns:
    Dictionary with a confirmation message including the path where the dish was stored

Inputs: dish_data (required).

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

Loading tool schema changelog…

    TDQS

    B3.2/5.0

    Scored across 8 tools

    Disambiguation5/5

    Each tool targets a distinct action and resource: adding/listing ignored ingredients, storing/listing dishes, creating/listing meal plans, generating grocery lists, and exporting PDFs. No two tools have overlapping purposes.

    Naming Consistency5/5

    All tool names follow a consistent verb_noun pattern in snake_case (e.g., add_ignored_ingredient, list_dishes, generate_grocery_list). There are no style mix-ups or ambiguous verbs.

    Tool Count5/5

    Eight tools is well-scoped for a meal planning server. The set covers the main operations without being too sparse or bloated, making it easy for agents to navigate.

    Completeness2/5

    The tool set lacks update and delete operations for all resources (dishes, meal plans, grocery lists, ignored ingredients), and there is no way to retrieve a single dish or meal plan by ID. These gaps significantly limit the agent's ability to manage meal data fully.

    Maintenance

    ActivityInactive
    ResponsivenessNo recent community issues

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