mcp-perplexity-search: Seamless Integration & Enhanced Context

Key Features of mcp-perplexity-search: Seamless Integration & Enhanced Context?

• Pre-configured prompt templates for common tasks (documentation generation, security analysis)
• Automatic context management across API calls
• Support for multi-turn conversations with session persistence
• Output format flexibility (JSON, markdown, raw text)
• Rate limiting and error handling middleware

Use Cases of mcp-perplexity-search: Seamless Integration & Enhanced Context?

Common applications include:

• Automated technical documentation generation from code comments
• Real-time security policy analysis for compliance reporting
• Chatbot backends requiring contextual understanding
• Automated code review with AI-driven suggestions
• Multi-lingual customer support systems

FAQ from mcp-perplexity-search: Seamless Integration & Enhanced Context?

How do I handle API rate limits?

Configure the rateLimiter middleware option in your server setup

Can I use this with custom models?

Currently supports Perplexity SONAR models only - extension hooks available for future integrations

What authentication methods are supported?

Accepts API keys via header or environment variables with OAuth 2.0 compatibility planned

How is context maintained between requests?

Uses session tokens to track conversation history up to the configured memory window

Is there a free tier available?

Dependent on Perplexity's pricing plans - see official pricing page

mcp-perplexity-search

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

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)

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

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

MIT License - see the LICENSE file for details.

Acknowledgments

• Built on the Model Context Protocol
• Powered by Perplexity SONAR