Cc Peng MCP

An MCP server for intelligently optimizing Claude code prompts, featuring automatic language task detection, interactive optimization, and no API dependency.

Developer tools Artificial intelligence chatbots #Prompt optimization #Interactive #No API #Code enhancement .TypeScript

rating : 2 points

downloads : 4.2K

update time : 2025-08-15

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Installation

Copy the following command to your Client for configuration

{
  "mcpServers": {
    "prompt-engineer": {
      "command": "node",
      "args": ["/absolute/path/to/cc_peng_mcp/index.ts"],
      "env": {}
    }
  }
}

Note: Your key is sensitive information, do not share it with anyone.

🚀 Claude Code Prompt Engineer MCP Server

An advanced Model Context Protocol (MCP) server that intelligently engineers and optimizes prompts for Claude Code. It comes with interactive refinement capabilities and automatic optimization, enhancing the efficiency and quality of prompt usage.

✨ Features

🚀 Intelligent Prompt Engineering

Automatically detects the programming language and task type.
Optimizes prompts according to Claude Code's capabilities.
Utilizes knowledge of Claude Code's tools and workflows.

🤖 Interactive Refinement

Features a Q&A-based prompt clarification system.
Generates context-aware questions.
Implements a session-based refinement process.

⚡ Automatic Optimization

Enhances prompts specific to the language.
Detects task complexity.
Is aware of Claude Code's capabilities.
No external API dependencies - operates entirely with built-in capabilities.

📦 Installation

1. Install Dependencies

npm install

2. Configure Claude Code

Create or update your .mcp.json configuration file:

{
  "mcpServers": {
    "prompt-engineer": {
      "command": "node",
      "args": ["/absolute/path/to/cc_peng_mcp/index.ts"],
      "env": {}
    }
  }
}

3. Restart Claude Code

# Exit current session and start new one
claude

4. Verify Installation

/mcp

You should see prompt-engineer listed as connected.

💻 Usage Examples

🎯 Auto-Optimization (Primary Usage)

Simply use the tools directly - no setup required:

Use the auto_optimize tool to analyze: "fix my React app performance issues"

Interactive Mode for Complex Requests

Use the engineer_prompt tool with interactive=true for: "create a new authentication system"

Direct Prompt Engineering

Use the engineer_prompt tool with prompt="optimize my database queries" and language="python"

📚 Documentation

Available Tools

`auto_optimize` ⭐ Primary Tool

Automatically detects and optimizes natural language text:

text (required): Your natural language text/request
context (optional): Additional project context
interactive (optional): Force interactive questioning

`engineer_prompt`

Manual prompt engineering with specific parameters:

prompt (required): The raw user prompt that needs engineering
language (optional): Programming language (auto-detected if not provided)
context (optional): Additional project context
interactive (optional): Enable Q&A refinement process

`answer_questions`

Used to provide answers during interactive sessions:

sessionId (required): Session ID from interactive mode
answers (required): Array of answers to the questions

How It Works

1. Natural Language Detection

The system automatically identifies when your text is natural language that needs optimization by detecting:

Request patterns: "help me", "can you", "i need", "i want"
Problem descriptions: "issue", "bug", "not working", "broken"
Task indicators: "create", "build", "fix", "optimize"
Questions: "how do", "what is", "why is"
Conversational markers: "i'm", "i think", "not sure"

2. Built-in Intelligence

No API calls required - uses pattern matching and rule-based optimization
Language detection via regex patterns for 10+ programming languages
Task type detection (debug, test, refactor, explain, architecture)
Complexity analysis based on text length and technical indicators

3. Claude Code Optimization

Prompts are optimized knowing Claude Code's capabilities:

File system operations (Read, Write, Edit)
Code search (Grep, Glob patterns)
Git operations and workflow management
Todo list management for complex tasks
Browser automation via Playwright MCP
GitHub integration

4. Interactive Refinement

When needed, the system:

Generates clarifying questions based on your prompt
Creates a session to track the conversation
Refines the prompt based on your answers
Delivers a highly optimized final prompt

Example Workflows

🎯 Auto-Optimization Example

Input:

"my website is slow and users are complaining"

Auto-Optimized Output:

**Task:** Debug and fix the following issue:

my website is slow and users are complaining

**Requirements:**
- Use file search tools (Grep/Glob) to locate relevant code
- Read and analyze the problematic files
- Identify the root cause and implement a fix
- Test the solution if possible

**Ready to proceed with this task?**

🤖 Interactive Mode Example

Input: "make my app better"

Questions Generated:

What specific aspect needs improvement (performance, readability, maintainability)?
What technology stack or programming language are you using?
Are there any constraints or requirements I should know about?

After Answers: Creates detailed, structured prompt with your specific requirements.

Benefits

✅ No Setup Required: Works immediately after MCP configuration
✅ No API Keys: Uses only built-in Claude Code capabilities
✅ Context Aware: Understands your project and requirements
✅ Interactive: Asks clarifying questions when needed
✅ Systematic: Structures complex requests properly
✅ Fast: No external API calls for instant optimization