MCP Perplexity Search

# 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. <a href="https://glama.ai/mcp/servers/zlqdizpsr9"> <img width="380" height="200" src="https://glama.ai/mcp/servers/zlqdizpsr9/badge" /> </a> ## 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: ```json { "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: ```json { "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: ```bash pnpm install ``` 3. Build the project: ```bash pnpm build ``` 4. Run in development mode: ```bash pnpm dev ``` ### Publishing The project uses changesets for version management. To publish: 1. Create a changeset: ```bash pnpm changeset ``` 2. Version the package: ```bash pnpm changeset version ``` 3. Publish to npm: ```bash pnpm release ``` ## Contributing Contributions are welcome! Please feel free to submit a Pull Request. ## License MIT License - see the [LICENSE](LICENSE) file for details. ## Acknowledgments - Built on the [Model Context Protocol](https://github.com/modelcontextprotocol) - Powered by [Perplexity SONAR](https://docs.perplexity.ai/api-reference/chat-completions)