mcp-perplexity-search

⚠️ Notice

This repository is no longer maintained.

The functionality of this tool is now available in mcp-omnisearch, which combines multiple MCP tools in one unified package.

Please use mcp-omnisearch instead.

A Model Context Protocol (MCP) server for integrating Perplexity's AI API with LLMs. This server provides advanced chat completion capabilities with specialized prompt templates for various use cases.

Features

• 🤖 Advanced chat completion using Perplexity's AI models
• 📝 Predefined prompt templates for common scenarios:
  • Technical documentation generation
  • Security best practices analysis
  • Code review and improvements
  • API documentation in structured format
• 🎯 Custom template support for specialized use cases
• 📊 Multiple output formats (text, markdown, JSON)
• 🔍 Optional source URL inclusion in responses
• ⚙️ Configurable model parameters (temperature, max tokens)
• 🚀 Support for various Perplexity models including Sonar and LLaMA

API

The server implements a single MCP tool with configurable parameters:

chat_completion

Generate chat completions using the Perplexity API with support for specialized prompt templates.

Parameters:

• messages (array, required): Array of message objects with:
  • role (string): 'system', 'user', or 'assistant'
  • content (string): The message content
• prompt_template (string, optional): Predefined template to use:
  • technical_docs: Technical documentation with code examples
  • security_practices: Security implementation guidelines
  • code_review: Code analysis and improvements
  • api_docs: API documentation in JSON format
• custom_template (object, optional): Custom prompt template with:
  • system (string): System message for assistant behaviour
  • format (string): Output format preference
  • include_sources (boolean): Whether to include sources
• format (string, optional): 'text', 'markdown', or 'json' (default: 'text')
• include_sources (boolean, optional): Include source URLs (default: false)
• model (string, optional): Perplexity model to use (default: 'sonar')
• temperature (number, optional): Output randomness (0-1, default: 0.7)
• max_tokens (number, optional): Maximum response length (default: 1024)

Development

Setup

1. Clone the repository
2. Install dependencies:

pnpm install

3. Build the project:

pnpm build

4. Run in development mode:

pnpm dev

Publishing

The project uses changesets for version management. To publish:

1. Create a changeset:

pnpm changeset

2. Version the package:

pnpm changeset version

3. Publish to npm:

pnpm release

Configuration

This server requires configuration through your MCP client. Here are examples for different environments:

Cline Configuration

Add this to your Cline MCP settings:

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

Claude Desktop with WSL Configuration

For WSL environments, add this to your Claude Desktop configuration:

{
	"mcpServers": {
		"mcp-perplexity-search": {
			"command": "wsl.exe",
			"args": [
				"bash",
				"-c",
				"source ~/.nvm/nvm.sh && PERPLEXITY_API_KEY=your-perplexity-api-key /home/username/.nvm/versions/node/v20.12.1/bin/npx mcp-perplexity-search"
			]
		}
	}
}

Environment Variables

The server requires the following environment variable:

• PERPLEXITY_API_KEY: Your Perplexity API key (required)

License

MIT License - see the LICENSE file for details.