Database · MODEL CONTEXT PROTOCOL

Coding Prompt Engineer MCP Server

Write 10x better prompts using Prompt Engineer MCP server.

WHAT IT CONNECTS

What Coding Prompt Engineer MCP Server gives an AI Agent

The source catalog does not include a structured feature list. Review the repository documentation before use.

SECURITY

An MCP listing is not a security review

An MCP server may receive model context, credentials, local files, or permission to call external systems. Review its code, requested environment variables, network behavior, package provenance, and maintenance status before connecting it to an agent.

README

Repository documentation

Coding Prompt Engineer MCP Server

This Model Context Protocol (MCP) server provides a tool to rewrite coding prompts for optimal results with Cursor AI and other AI IDEs, using Claude by Anthropic.

Installation

npm install

Install via Smithery

You can install this MCP server directly through Smithery by visiting: https://smithery.ai/server/@hireshBrem/prompt-engineer-mcp-server

Usage

Setting Environment Variables

The server requires an Anthropic API key to use Claude for formatting. Set it as an environment variable:

export ANTHROPIC_API_KEY=your_anthropic_api_key

If no API key is provided, the server will throw an error indicating the missing API key.

Running the Server

npm start

Or with MCP Inspector:

npx @modelcontextprotocol/inspector npm start

Tool: rewrite_coding_prompt

This tool takes a raw prompt and rewrites it for optimal results with Cursor AI and other AI IDEs.

Parameters

  • prompt (required): The raw user's prompt that needs rewriting
  • language (required): The programming language of the code

Example Usage

{
  "name": "rewrite_coding_prompt",
  "arguments": {
    "prompt": "Create a function to convert temperature between Celsius and Fahrenheit",
    "language": "typescript"
  }
}

How It Works

The server uses Claude 3 Sonnet by Anthropic to intelligently rewrite your prompts for better results. It enhances your prompt by:

  1. Adding clear structure and context
  2. Specifying requirements and expectations
  3. Including language-specific considerations
  4. Optimizing for AI IDE understanding

Features

  • Intelligent Prompt Engineering: Uses Claude 3 Sonnet to rewrite prompts for optimal results
  • Language-Aware: Customizes prompts based on target programming language
  • Easy Integration: Works seamlessly with Cursor and other AI IDEs
  • Low Temperature Setting: Uses 0.2 temperature for consistent, structured output

Configuration

Usage with Claude Desktop

Add this to your claude_desktop_config.json:

NPX

{
  "mcpServers": {
    "cursor-prompt-engineer": {
      "command": "npx",
      "args": [
        "-y",
        "cursor-prompt-engineer"
      ]
    }
  }
}

Local Installation

# Clone the repository
git clone https://github.com/yourusername/cursor-prompt-engineer.git
cd cursor-prompt-engineer

# Install dependencies
npm install

# Run the server
node index.js

Example

Input:

Create a function that sorts an array of objects by a specific property

With arguments:

{
  "prompt": "Create a function that sorts an array of objects by a specific property",
  "language": "typescript"
}

The tool will rewrite the prompt to be more structured and detailed for optimal results with your AI IDE.

License

This MCP server is licensed under the MIT License. This means you are free to use, modify, and distribute the software, subject to the terms and conditions of the MIT License. For more details, please see the LICENSE file in the project repository.

View README on GitHub

COMMUNITY

Save, rate, and discuss

Loading community data…