Prompt Explorer Server

A comprehensive Model Context Protocol (MCP) server that demonstrates the prompt feature with 10 different development-focused prompts. This server is perfect for exploring how MCP prompts work and can be integrated into LLM applications like Claude Desktop.

📋 What are MCP Prompts?

MCP prompts are pre-configured, reusable templates that LLM applications can use. They:

• Standardize common tasks: Create consistent workflows
• Accept arguments: Dynamic prompts that adapt to your needs
• Provide structure: Well-formatted prompts for better results
• Save time: No need to craft prompts from scratch

✨ Features

This server includes 10 powerful prompts:

1. 🔍 code-review - Comprehensive code review with focus areas
2. 📚 explain-concept - Technical concept explanation with examples
3. 🐛 debug-assistant - Debug code with error analysis
4. 📖 api-documentation - Generate API documentation
5. ♻️ refactor-suggestion - Code refactoring recommendations
6. 🧪 test-generator - Generate unit tests
7. 🏗️ architecture-review - System architecture analysis
8. 💬 git-commit-message - Generate commit messages
9. ⚡ sql-optimizer - SQL query optimization
10. 🎓 learning-path - Personalized learning paths

🚀 Quick Start

Prerequisites

• Python 3.10 or higher
• pip or uv package manager

Installation

Option 1: Using UV (Recommended)

# Install UV if you haven't already
pip install uv

# Create and activate virtual environment
uv venv
source .venv/bin/activate  # On Windows: .venv\Scripts\activate

# Install dependencies
uv pip install mcp

Option 2: Using pip

# Create virtual environment
python -m venv .venv
source .venv/bin/activate  # On Windows: .venv\Scripts\activate

# Install dependencies
pip install mcp

Running the Server

uv run server.py

🔧 Integration with Claude Desktop

To use this server with Claude Desktop, add it to your configuration:

macOS/Linux Configuration

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

{
  "mcpServers": {
    "prompt-explorer": {
      "command": "python",
      "args": ["/absolute/path/to/mcp_prompt_explorer_server.py"],
      "env": {}
    }
  }
}

Windows Configuration

Edit %APPDATA%\Claude\claude_desktop_config.json:

{
  "mcpServers": {
    "prompt-explorer": {
      "command": "python",
      "args": ["C:\\absolute\\path\\to\\mcp_prompt_explorer_server.py"],
      "env": {}
    }
  }
}

Important: Replace /absolute/path/to/ with the actual path where you saved the server file.

Using with UV (Alternative)

If using UV, you can configure it like this:

{
  "mcpServers": {
    "prompt-explorer": {
      "command": "uv",
      "args": [
        "run",
        "--with",
        "mcp",
        "python",
        "/absolute/path/to/mcp_prompt_explorer_server.py"
      ]
    }
  }
}

📖 Usage Examples

Once integrated with Claude Desktop, you can use prompts like this:

Example 1: Code Review

Use the code-review prompt with this Python code:

def calculate(a, b):
    return a + b

The prompt will automatically format a comprehensive code review request.

Example 2: Explain a Concept

Use the explain-concept prompt to explain "async/await in Python" 
for a beginner audience with code examples

Example 3: Debug Assistance

Use the debug-assistant prompt with this error:
"TypeError: unsupported operand type(s) for +: 'int' and 'str'"

And this code:
x = 5
y = "10"
result = x + y

Example 4: Generate Tests

Use the test-generator prompt with comprehensive coverage 
for this function:

def factorial(n):
    if n <= 1:
        return 1
    return n * factorial(n - 1)

🎯 Understanding Prompt Arguments

Each prompt has specific arguments:

Required Arguments

These must be provided for the prompt to work.

Optional Arguments

These customize the prompt behavior but have defaults.

Example from the code-review prompt:

• code (required) - The code to review
• language (optional) - Programming language
• focus (optional) - Specific focus area

🔍 Exploring the Code

Key Components

1. list_prompts() - Returns all available prompts

   • Called when client queries available prompts
   • Returns prompt metadata including arguments

2. get_prompt() - Returns a specific prompt with arguments filled in

   • Takes prompt name and argument values
   • Returns formatted prompt message

3. Prompt Structure:

   Prompt(
       name="prompt-name",
       description="What this prompt does",
       arguments=[
           PromptArgument(
               name="arg_name",
               description="What this argument is for",
               required=True/False,
           ),
       ],
   )
   

🛠️ Customizing Prompts

Want to add your own prompts? Here's how:

1. Add to list_prompts():

   Prompt(
       name="my-custom-prompt",
       description="My awesome prompt",
       arguments=[
           PromptArgument(
               name="input",
               description="Input data",
               required=True,
           ),
       ],
   )
   

2. Add handler in get_prompt():

   elif name == "my-custom-prompt":
       input_data = arguments.get("input", "")
       return GetPromptResult(
           description="Custom prompt result",
           messages=[
               PromptMessage(
                   role="user",
                   content=TextContent(
                       type="text",
                       text=f"Process this: {input_data}"
                   ),
               ),
           ],
       )
   

📚 Learning Resources

• MCP Documentation
• MCP Specification
• MCP Python SDK

🎨 Prompt Best Practices

Based on this server's implementation:

1. Clear Structure: Use numbered lists and headers
2. Specific Instructions: Be explicit about what you want
3. Examples: Provide examples when helpful
4. Formatting: Use XML tags or markdown for clarity
5. Flexibility: Support optional arguments with sensible defaults

🐛 Troubleshooting

Server Not Showing Up in Claude Desktop

1. Check configuration file syntax (valid JSON)
2. Verify absolute path to server file
3. Ensure Python/UV is in PATH
4. Restart Claude Desktop after configuration changes
5. Check Claude Desktop logs

Import Errors

# Make sure mcp is installed
pip install mcp
# or
uv add mcp

Python Version Issues

Ensure you're using Python 3.10+:

python --version

💡 Tips for Using Prompts

1. Start Simple: Try prompts with just required arguments
2. Add Details: Use optional arguments to refine results
3. Iterate: Adjust arguments based on results
4. Combine: Use multiple prompts for complex tasks

🔄 What's Next?

Try these exercises to learn more about MCP prompts:

1. Modify an existing prompt template
2. Add a new prompt for your specific use case
3. Combine prompts in workflows
4. Create argument validation logic
5. Add multi-turn conversation prompts

📝 License

This is a demonstration project for learning about MCP prompts. Feel free to use, modify, and extend it!

🤝 Contributing

This is a learning project! Feel free to:

• Add new prompts
• Improve existing templates
• Add features (resources, tools)
• Share your customizations

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Happy Prompting! 🎉

Need help? The code is heavily commented to help you understand how everything works.