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RISEN Prompt Engineering MCP Tool

MIT License
  • Apple

RISEN Prompt Engineering MCP Tool

A powerful Model Context Protocol (MCP) server that helps you create, validate, manage, and optimize prompts using the RISEN framework.

What is RISEN?

RISEN is a structured prompt engineering framework with 5 components:

  • Role: Define the AI's persona/expertise
  • Instructions: Clear directives for the task
  • Steps: Breakdown of the process
  • Expectations: Desired outcome/format
  • Narrowing: Constraints or creative elements

Features

🎯 Core Functionality

  • Template Management: Create, store, and organize RISEN prompt templates
  • Variable Support: Use {{variables}} for dynamic, reusable prompts
  • Validation Engine: Real-time structure checking and quality scoring
  • Performance Tracking: Monitor prompt effectiveness with ratings and analytics
  • AI Suggestions: Get improvement recommendations based on best practices

🚀 Advanced Features

  • A/B Testing: Compare different prompt variations
  • Cross-AI Integration: Works with your Cross-AI tool to test prompts on multiple models
  • Knowledge Base Integration: Save successful prompts for future reference
  • Natural Language Conversion: Transform regular requests into RISEN format
  • Template Library: Pre-built templates for common tasks

Installation

  1. Clone the repository:
git clone https://github.com/YOUR_USERNAME/mcp-risen-prompts.git cd mcp-risen-prompts
  1. Install dependencies:
npm install
  1. Test the server:
npm test
  1. The server is now ready to be configured in Claude Desktop

Configuration

Add to your Claude Desktop config:

macOS

~/Library/Application Support/Claude/claude_desktop_config.json

Windows

%APPDATA%\Claude\claude_desktop_config.json

{ "mcpServers": { "risen-prompts": { "command": "node", "args": ["/path/to/mcp-risen-prompts/server.js"] } } }

Usage Examples

Creating a Template

Use risen_create to make a new template: - Name: "Code Review" - Role: "Senior software engineer with 15+ years experience" - Instructions: "Review the provided code for quality and security" - Steps: ["Analyze structure", "Check for bugs", "Suggest improvements"] - Expectations: "Detailed line-by-line feedback with examples" - Narrowing: "Focus on critical issues first"

Executing a Template

Use risen_execute with variables: - Template ID: [your-template-id] - Variables: {"language": "Python", "framework": "Django"}

Tracking Performance

After using a prompt, track its effectiveness: - Use risen_track - Rate 1-5 stars - Add notes about what worked/didn't work

MCP Tools Available

  1. risen_create - Create new RISEN templates
  2. risen_validate - Check structure and get suggestions
  3. risen_execute - Run templates with variables
  4. risen_track - Record performance metrics
  5. risen_search - Find templates by tags/rating
  6. risen_analyze - Get insights on template performance
  7. risen_suggest - AI-powered improvement recommendations
  8. risen_convert - Transform natural language to RISEN

Template Examples

Blog Post Writer

Role: Content strategist and SEO expert Instructions: Write an engaging blog post about {{topic}} Steps: 1. Research keywords and trends 2. Create compelling headline 3. Develop main points with examples 4. Include statistics and sources 5. Write conclusion with CTA Expectations: 1500-2000 words, SEO-optimized, engaging tone Narrowing: Use conversational tone, include 3-5 keywords naturally

Data Analysis

Role: Data scientist specializing in {{domain}} Instructions: Analyze {{dataset}} to uncover insights Steps: 1. Perform exploratory data analysis 2. Identify key trends and patterns 3. Run statistical tests 4. Create visualizations 5. Provide recommendations Expectations: Clear insights with statistical backing Narrowing: Focus on {{specific_metrics}} and business impact

Quality Scoring

Templates are scored out of 100 based on:

  • Role specificity (20 points)
  • Instruction clarity (20 points)
  • Step detail (20 points)
  • Expectation metrics (20 points)
  • Narrowing focus (20 points)

Best Practices

  1. Be Specific: Vague roles like "assistant" score lower than "Senior Python developer with AWS expertise"
  2. Use Variables: Make templates reusable with {{variables}}
  3. Measurable Expectations: Include numbers (word count, examples needed, etc.)
  4. Clear Steps: Each step should be actionable and specific
  5. Test & Iterate: Use tracking to refine templates over time

Integration with Other MCP Tools

With Cross-AI Tool

Execute the same RISEN prompt across multiple AI models:

  1. Create/select a RISEN template
  2. Use Cross-AI to run it on ChatGPT, Gemini, and Claude
  3. Compare results and track which model performs best

With Knowledge Base

Save successful prompts for future reference:

  1. Create and test a RISEN prompt
  2. Once proven effective, save to Knowledge Base
  3. Search and retrieve proven prompts by topic

Troubleshooting

Template not validating?

  • Ensure all required fields are filled
  • Check that steps is an array, not a string
  • Verify variables are properly declared

Variables not replacing?

  • Use exact syntax: {{variable_name}}
  • Ensure variable names match in declaration and usage
  • Check that all variables have values when executing

Low quality scores?

  • Add more detail to each component
  • Include specific metrics in expectations
  • Use domain-specific language in role

Future Roadmap

  • Visual template builder UI
  • Community template marketplace
  • Advanced analytics dashboard
  • Prompt chaining workflows
  • Export/import template packs
  • Team collaboration features

Contributing

Found a bug or have a feature request? Feel free to contribute!

License

MIT License - feel free to use and modify as needed.

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