What is Mcp Perplexity Server

The mcp-perplexity-server is a Model Context Protocol (MCP) server designed for intelligent code analysis and debugging, utilizing Perplexity AI’s API and integrated with the Claude desktop client.

Use cases

Use cases for the mcp-perplexity-server include debugging Python code, understanding error messages, and receiving tailored solutions for coding issues, making it ideal for developers seeking efficient error resolution.

How to use

To use the mcp-perplexity-server, install it via npm or from source, configure it in the Claude desktop client, and then input your code snippets along with specific queries related to errors or debugging.

Key features

Key features include intelligent error analysis, pattern detection for common coding errors, comprehensive solutions with step-by-step fixes, best practices for coding standards, and specialized support for Python.

Where to use

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Perplexity MCP Server

A Model Context Protocol (MCP) server that provides intelligent code analysis and debugging capabilities using Perplexity AI’s API. Works seamlessly with the Claude desktop client.

Features

• Intelligent Error Analysis: Detailed breakdown of coding errors with root cause analysis
• Pattern Detection: Automatically recognizes common error patterns and provides targeted solutions
• Comprehensive Solutions: Step-by-step fixes with multiple implementation alternatives
• Best Practices: Includes coding standards and error prevention tips
• Python Support: Specialized handling of Python type errors and common coding issues

Example Usage

Ask questions like:

• “Fix this TypeError in my Python code”
• “What’s causing this error message?”
• “How do I fix this code?”

Include your code snippet for targeted analysis:

def calculate_total(items):
    total = 0
    for item in items:
        total = total + item['price']  # TypeError: string + int

data = [
    {'name': 'Book', 'price': '10'},
    {'name': 'Pen', 'price': '2'}
]

result = calculate_total(data)

The server will provide:

1. Root cause analysis of the error
2. Step-by-step solution with code examples
3. Best practices to prevent similar issues
4. Alternative implementation approaches

Installation

Prerequisites

• Node.js 18 or higher
• A Perplexity AI API key

Option 1: Install from npm (Recommended)

# Using npm
npm install -g perplexity-mcp

# Or using the repository directly
npm install -g git+https://github.com/yourusername/perplexity-mcp.git

Option 2: Install from Source

1. Clone the repository:

git clone https://github.com/yourusername/perplexity-server.git
cd perplexity-server

2. Install dependencies:

npm install

3. Build and install globally:

npm run build
npm install -g .

Configure Claude Desktop

Add to your Claude desktop configuration file:

MacOS: ~/Library/Application Support/Claude/claude_desktop_config.json
Windows: %APPDATA%/Claude/claude_desktop_config.json

{
  "mcpServers": {
    "perplexity": {
      "command": "perplexity-mcp",
      "args": [],
      "env": {
        "PERPLEXITY_API_KEY": "your-api-key-here"
      }
    }
  }
}

Or if installed from source:

{
  "mcpServers": {
    "perplexity": {
      "command": "node",
      "args": [
        "/absolute/path/to/perplexity-server/build/index.js"
      ],
      "env": {
        "PERPLEXITY_API_KEY": "your-api-key-here"
      }
    }
  }
}

Security

• The API key is stored securely in Claude’s desktop configuration file
• The key is passed to the server as an environment variable
• No sensitive data is stored in the repository
• The server expects the API key to be provided by Claude’s environment

Development

Project Structure

perplexity-server/
├── src/
│   └── index.ts      # Main server implementation
├── package.json      # Project configuration
└── tsconfig.json    # TypeScript configuration

Available Scripts

• npm run build: Build the project
• npm run watch: Watch for changes and rebuild automatically
• npm run prepare: Prepare the package for publishing
• npm run inspector: Run the MCP inspector for debugging

Contributing

1. Fork the repository
2. Create your feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add some amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

License

This project is licensed under the MIT License - see the LICENSE file for details.

Acknowledgments

• Thanks to Perplexity AI for their powerful API
• Built with Model Context Protocol