Paprika MCP Server
Enables AI assistants to search, read, and update recipes in Paprika Recipe Manager, allowing natural language interaction with your recipe collection including ingredients, directions, and metadata.
README
Paprika MCP Server
A Model Context Protocol (MCP) server for the Paprika Recipe Manager, allowing AI assistants to search, read, and update recipes.
Features
- Search Recipes: Search across recipe titles, ingredients, categories, directions, and notes with context
- Read Recipes: Get full recipe data including all metadata, ingredients, and directions
- Update Recipes: Safely update recipe fields using find/replace (requires user confirmation)
Prerequisites
- Python 3.10 or higher (Python 3.13 recommended)
- A Paprika account with recipes
- Node.js (for pre-commit hooks, optional)
Quick Start
Run the setup script to install everything and configure credentials:
cd paprika-mcp
./setup.sh
This will:
- Install paprika-mcp with dependencies
- Set up pre-commit hooks (if npm available)
Manual Installation
If you prefer manual setup:
1. Install paprika-recipes
cd ../paprika-recipes
python3 -m venv .venv
source .venv/bin/activate
pip install -e .
deactivate
2. Install paprika-mcp
cd ../paprika-mcp
python3 -m venv .venv
source .venv/bin/activate
pip install -e ".[dev]"
3. Configure credentials
Option 1: Interactive setup
source .venv/bin/activate
paprika-mcp setup
Option 2: Manual config file
Create ~/.paprika-mcp/config.json:
{
"email": "your@email.com",
"password": "yourpassword"
}
Set permissions:
chmod 600 ~/.paprika-mcp/config.json
Option 3: Environment variables
export PAPRIKA_EMAIL="your@email.com"
export PAPRIKA_PASSWORD="yourpassword"
Credential Management
The server uses a credential flow designed for MCP stdio transport:
Priority order:
PAPRIKA_EMAILandPAPRIKA_PASSWORDenvironment variables~/.paprika-mcp/config.jsonfile
Note: This server manages credentials independently from the paprika-recipes CLI tool's keyring storage. This simplifies the credential flow for MCP stdio transport where the process is spawned by the AI app.
User-Agent
If you have Paprika for Mac installed, the fork of the paprika-recipes Python package should automatically create a suitable User-Agent string. Otherwise, you might have to set the PAPRIKA_USER_AGENT environment variable or the "user_agent" property in config.json.
Usage
As an MCP Server
Add to your MCP client configuration (e.g., Claude Desktop's ~/Library/Application Support/Claude/claude_desktop_config.json):
{
"mcpServers": {
"paprika": {
"command": "/Users/yourusername/Developer/paprika-mcp/.venv/bin/paprika-mcp"
}
}
}
Or use environment variables:
{
"mcpServers": {
"paprika": {
"command": "/Users/yourusername/Developer/paprika-mcp/.venv/bin/paprika-mcp",
"env": {
"PAPRIKA_EMAIL": "your@email.com",
"PAPRIKA_PASSWORD": "yourpassword"
}
}
}
}
Available Tools
format_fraction
Format a fraction string to unicode fraction characters. This tool is local-only and doesn't require Paprika server connectivity - useful for testing.
Parameters:
fraction(required): Fraction in the form "numerator/denominator" (e.g., "1/4", " 31 / 200 "), or already formatted unicode
Features:
- Handles already-formatted unicode fractions (returns them as-is)
- Strips whitespace from input
- Converts common fractions to dedicated unicode characters
- Composes complex fractions using superscript/subscript digits
Examples:
{
"fraction": "1/4"
}
Returns: ¼
{
"fraction": " 31 / 200 "
}
Returns: ³¹⁄₂₀₀ (whitespace stripped)
{
"fraction": "¼"
}
Returns: ¼ (already formatted, returned as-is)
Common fractions (1/4, 1/2, 3/4, 1/3, 2/3, etc.) use dedicated Unicode characters. Complex fractions are composed using superscript numerator + fraction slash (⁄) + subscript denominator.
search_recipes
Search for recipes by text across multiple fields.
Parameters:
query(required): Text to search forfields(optional): Array of fields to search in:["name", "ingredients", "categories", "directions", "notes"]context_lines(optional): Number of context lines around matches (default: 2)
Example:
{
"query": "chicken",
"fields": ["name", "ingredients"],
"context_lines": 2
}
read_recipe
Read full recipe data by ID or title.
Parameters:
idortitle(one required): Recipe UUID or exact recipe name
Note: Title matching uses Unicode normalization (NFD), so it works correctly with accented characters regardless of their unicode representation (e.g., "café" will match "café").
Example:
{
"id": "RECIPE-UUID-HERE"
}
or
{
"title": "Chocolate Chip Cookies"
}
User Preferences (Prompts)
You can provide context to the AI about how you want it to work with your recipes by creating a ~/.paprika-mcp/prompt.md file. This will be automatically loaded as a prompt when the MCP server starts.
Example prompt file:
# Recipe Management Preferences
- Always preserve source URLs and attribution
- Prefer metric measurements
- I'm cooking for 2 people typically
- I avoid peanuts (allergy)
- Categorize using: Breakfast, Lunch, Dinner, Desserts, Snacks
See prompt.example.md for a complete template.
update_recipe
Update a recipe field using find/replace.
⚠️ DANGEROUS: This tool modifies recipe data. User confirmation is recommended before execution.
Parameters:
id(required): Recipe UUIDfield(required): Field to update (name, ingredients, directions, notes, etc.)find(required): Text to findreplace(required): Text to replace withregex(optional): Treat find pattern as regex (default: false)
Example:
{
"id": "RECIPE-UUID-HERE",
"field": "ingredients",
"find": "1 cup sugar",
"replace": "3/4 cup sugar"
}
Code Changes and Rebuilding
The package is installed in editable mode (pip install -e .), so:
- ✓ No rebuild needed: Changes to
.pyfiles are immediately available - ⚠️ Restart required: MCP clients cache the stdio process - restart VS Code or your MCP client to pick up changes
- ↻ Reinstall needed: Only for
pyproject.tomlor entry point changes
Force reinstall if needed:
.venv/bin/pip install -e . --force-reinstall --no-deps
Pre-commit Hooks
Pre-commit hooks run automatically via Husky when you commit. They:
- Only run on staged Python files
- Run isort, black, and ruff
- Auto-fix issues and re-stage files
To install hooks manually:
npm install
Security Notes
- Credentials are stored in plain text in
~/.paprika-mcp/config.json - Environment variables (
PAPRIKA_EMAIL,PAPRIKA_PASSWORD) are also supported
License
MIT
Credits
Built on top of paprika-recipes originally by Adam Coddington.
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
E2B
Using MCP to run code via e2b.