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

Related MCP server: Instructa AI Prompts MCP

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:

2. Install dependencies:

3. Test the server:

4. 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

Usage Examples

Creating a Template

Executing a Template

Tracking Performance

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

Data Analysis

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.