Cookwith▌
by blaideinc
Cookwith: AI-powered recipe generation and transformation—create, adapt, and personalize recipes in seconds.
Recipe generation and transformation tools powered by Cookwith's culinary AI
Both formats append explainx.ai attribution and the canonical URL for this MCP server listing.
best for
- / Food bloggers and content creators
- / Cooking apps and recipe platforms
- / Meal planning applications
- / Dietary restriction meal planning
capabilities
- / Generate recipes from ingredients
- / Transform existing recipes for dietary restrictions
- / Modify recipes for different serving sizes
- / Create recipe variations with ingredient substitutions
- / Generate cooking instructions and tips
what it does
Generates and transforms recipes using Cookwith's AI-powered culinary tools. Helps create recipes from scratch or modify existing ones based on dietary needs and preferences.
about
Cookwith is a community-built MCP server published by blaideinc that provides AI assistants with tools and capabilities via the Model Context Protocol. Cookwith: AI-powered recipe generation and transformation—create, adapt, and personalize recipes in seconds. It is categorized under ai ml, developer tools. This server exposes 2 tools that AI clients can invoke during conversations and coding sessions.
how to install
You can install Cookwith in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server supports remote connections over HTTP, so no local installation is required.
license
MIT
Cookwith is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.
readme
Cookwith MCP Server
An MCP (Model Context Protocol) server that provides AI-powered recipe generation and transformation tools using Cookwith's advanced culinary AI.
Features
- Recipe Generation: Create custom recipes from natural language descriptions
- Recipe Transformation: Modify existing recipes based on dietary needs, serving sizes, or other requirements
- Dietary Support: Handle allergies, dietary restrictions, and nutritional goals
- Smart Adaptations: Adjust for calories, protein targets, and serving counts
Installation
Via MCP Registry
npx @modelcontextprotocol/create-server install @cookwith/mcp-server
Via npm
npm install -g @cookwith/mcp-server
For Claude Desktop
Add to your Claude Desktop configuration:
macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
Windows: %APPDATA%\Claude\claude_desktop_config.json
{
"mcpServers": {
"cookwith": {
"command": "npx",
"args": ["@cookwith/mcp-server"]
}
}
}
Available Tools
generate_recipe
Generate a new recipe based on natural language instructions.
Parameters:
prompt(string, required): Natural language description of the desired recipedietaryRestrictions(array): Dietary restrictions (e.g., vegetarian, vegan, gluten-free)allergies(array): Ingredients to avoid due to allergiesdislikes(array): Foods the user doesn't likecalories(string): Target calories per servingprotein(string): Target protein in grams per servingservings(number): Number of servings (1-20, default: 4)
Example:
{
"prompt": "A healthy pasta dish with lots of vegetables",
"dietaryRestrictions": ["vegetarian"],
"calories": "500",
"servings": 2
}
transform_recipe
Transform or modify an existing recipe based on instructions.
Parameters:
recipe(object, required): The recipe to transformtitle(string): Recipe titledescription(string): Recipe descriptioningredients(array): List of ingredientsinstructions(array): Cooking instructionsservings(number): Number of servings- Additional optional fields for nutrition, timing, etc.
instructions(string, required): How to transform the recipecalories(string): New target calories per servingprotein(string): New target protein per servingservings(number): New number of servings
Example:
{
"recipe": {
"title": "Classic Spaghetti Carbonara",
"description": "Traditional Italian pasta dish",
"ingredients": ["400g spaghetti", "200g guanciale", "4 eggs", "100g pecorino"],
"instructions": ["Cook pasta", "Fry guanciale", "Mix eggs and cheese", "Combine"],
"servings": 4
},
"instructions": "Make it vegetarian and reduce calories",
"calories": "400"
}
Usage Examples
With Claude
Once configured, you can use natural language to interact with the tools:
"Generate a healthy dinner recipe for 2 people with chicken and vegetables, around 500 calories per serving"
"Transform this pasta recipe to be gluten-free and dairy-free"
Programmatic Usage
import { Client } from '@modelcontextprotocol/sdk';
const client = new Client({
name: 'my-app',
version: '1.0.0'
});
await client.connect('npx', ['@cookwith/mcp-server']);
// Generate a recipe
const result = await client.callTool('generate_recipe', {
prompt: 'Quick and healthy breakfast',
calories: '350',
servings: 1
});
Development
Building from Source
git clone https://github.com/blaideinc/cookwith-mcp
cd cookwith-mcp
npm install
npm run build
Running Locally
npm start
Testing
npm test
API Endpoint
The MCP server can also be accessed via HTTP at:
- Production:
https://cookwith.co/api/mcp - Development:
http://localhost:3000/api/mcp
License
MIT
Support
- GitHub Issues: https://github.com/blaideinc/cookwith-mcp/issues
- Website: https://cookwith.co
About Cookwith
Cookwith is an AI-powered cooking platform that generates personalized recipes based on your preferences, dietary restrictions, and taste profile. Learn more at cookwith.co.
FAQ
- What is the Cookwith MCP server?
- Cookwith is a Model Context Protocol (MCP) server profile on explainx.ai. MCP lets AI hosts (e.g. Claude Desktop, Cursor) call tools and resources through a standard interface; this page summarizes categories, install hints, and community ratings.
- How do MCP servers relate to agent skills?
- Skills are reusable instruction packages (often SKILL.md); MCP servers expose live capabilities. Teams frequently combine both—skills for workflows, MCP for APIs and data. See explainx.ai/skills and explainx.ai/mcp-servers for parallel directories.
- How are reviews shown for Cookwith?
- This profile displays 68 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.8 out of 5—verify behavior in your own environment before production use.
Use Cases▌
Extended AI Capabilities
Add new capabilities to Claude beyond text generation
Example
Access external data sources, execute code, interact with tools and services
Transform Claude from chatbot to action-taking agent
Context Enhancement
Provide Claude with access to relevant context and data
Example
Load project documentation, access knowledge bases, query databases
Get more accurate, context-aware responses
Workflow Automation
Automate multi-step workflows combining AI and external tools
Example
Research → Summarize → Create document → Send notification
Complete complex tasks end-to-end without manual steps
Implementation Guide▌
Prerequisites
- ›Claude Desktop 0.7.0+ or Cursor IDE with MCP support
- ›Basic understanding of MCP architecture and capabilities
- ›Access credentials for integrated services (if required)
- ›Willingness to experiment and iterate on configuration
Time Estimate
15-60 minutes depending on server complexity
Installation Steps
- 1.Install MCP server: npm install -g [package-name] or via GitHub
- 2.Add server configuration to ~/.claude/mcp.json
- 3.Provide required credentials and configuration
- 4.Restart Claude Desktop to load new server
- 5.Test basic functionality with simple prompts
- 6.Explore capabilities and experiment with use cases
- 7.Document successful patterns for reuse
Troubleshooting
- ⚠MCP server not loading: Check config syntax, verify installation
- ⚠Connection errors: Check network, firewall, credentials
- ⚠Feature not working: Read server docs, check required parameters
- ⚠Performance issues: Monitor resource usage, check for network latency
- ⚠Conflicts with other servers: Check port assignments, namespace collisions
Best Practices▌
✓ Do
- +Read server documentation thoroughly before setup
- +Start with simple use cases to validate functionality
- +Test in non-production environment first
- +Monitor resource usage and performance
- +Keep servers updated for bug fixes and new features
- +Document configuration for team members
- +Use environment variables for sensitive configuration
✗ Don't
- −Don't grant overly permissive access to MCP servers
- −Don't skip reading security considerations in docs
- −Don't expose sensitive data without proper controls
- −Don't run untrusted MCP servers without code review
- −Don't ignore error messages—investigate root cause
💡 Pro Tips
- ★Combine multiple MCP servers for powerful workflows
- ★Create custom MCP servers for your specific needs
- ★Share successful configurations with team
- ★Use MCP inspector for debugging
- ★Join MCP community for tips and troubleshooting
Technical Details▌
Architecture
Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.
Protocols
- Model Context Protocol (MCP)
- JSON-RPC 2.0
- stdio or HTTP transport
Compatibility
- Claude Desktop
- Cursor IDE
- Custom MCP clients
When to Use This▌
✓ Use When
Use when you need Claude to access external data, execute actions, or integrate with tools. Best for extending AI capabilities beyond conversation.
✗ Avoid When
Avoid when native integrations exist (use official APIs directly), for real-time critical systems, or when security/compliance requires zero external dependencies.
Integration▌
- →Tool composition: Chain multiple MCP tools in workflows
- →Context augmentation: Provide AI with relevant external data
- →Action delegation: Let AI execute tasks on external systems
- →Bidirectional sync: Keep AI context and external systems in sync
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
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Ratings
4.8★★★★★68 reviews- ★★★★★Pratham Ware· Dec 28, 2024
I recommend Cookwith for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
- ★★★★★Chaitanya Patil· Dec 24, 2024
We wired Cookwith into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
- ★★★★★Ama Choi· Dec 24, 2024
According to our notes, Cookwith benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
- ★★★★★Noah Okafor· Dec 24, 2024
We wired Cookwith into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
- ★★★★★Anika Chawla· Dec 16, 2024
I recommend Cookwith for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
- ★★★★★Olivia Yang· Dec 12, 2024
Cookwith has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
- ★★★★★Piyush G· Nov 15, 2024
Cookwith is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
- ★★★★★Charlotte Desai· Nov 15, 2024
Useful MCP listing: Cookwith is the kind of server we cite when onboarding engineers to host + tool permissions.
- ★★★★★Valentina Chawla· Nov 15, 2024
Cookwith is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
- ★★★★★Anika Agarwal· Nov 3, 2024
Strong directory entry: Cookwith surfaces stars and publisher context so we could sanity-check maintenance before adopting.
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