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RISEN Prompt Engineering MCP Server

RISEN Prompt Engineering MCP Server - A structured framework for creating, validating, and optimizing AI prompts using Role, Instructions, Steps, Expectations, and Narrowing components. Fully anonymous and ready for public use.

Installation
Add the following to your MCP client configuration file.

Configuration

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

You get a RISEN-based MCP server that helps you create, validate, manage, and optimize RISEN prompts. It streamlines template workflows, supports dynamic variables, and provides real‑time validation and analytics so you can improve prompt quality and performance across tasks.

How to use

Set up the RISEN prompts MCP on your machine and connect it to your MCP client. Start by launching the local server, then use your client to create, execute, and track RISEN templates. You can build templates with a defined Role, Instructions, Steps, Expectations, and Narrowing, supply variables for dynamic prompts, validate structure, run prompts with variables, and monitor performance over time.

How to install

Prerequisites: Node.js and npm must be installed on your system.

Clone the project and install dependencies, then run tests to verify the server is working.

git clone https://example.com/risen-prompts-mcp-server.git
cd risen-prompts-mcp-server
npm install
npm test

Configuration and usage notes

Configure the MCP client to connect to the RISEN prompts MCP server. Use the provided local runtime command to start the server so the MCP client can reach it.

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

Example workflows

Create a RISEN template using the risens tools, supply variables, validate the structure, and then execute with actual values. Track performance after use to see how ratings evolve and where to improve.

Available tools

risen_create

Create new RISEN templates by specifying Role, Instructions, Steps, Expectations, and Narrowing.

risen_validate

Validate RISEN templates for proper structure and receive improvement suggestions.

risen_execute

Run a RISEN template with a set of variables to generate a prompt output.

risen_track

Record performance metrics after using a RISEN prompt and store ratings and notes.

risen_search

Find templates by tags, rating, or keywords.

risen_analyze

Analyze template performance across usage data to derive insights.

risen_suggest

AI-powered recommendations to improve RISEN templates.

risen_convert

Transform natural language requests into RISEN format.