Perplexica MCP Server

Perplexica MCP Server is a Model Context Protocol (MCP) server that acts as a proxy to provide LLM access to Perplexica's AI-powered search engine. This server enables AI assistants and other MCP clients to perform searches through the Perplexica API.

What This MCP Server Provides

• Single Search Tool: Exposes Perplexica's search functionality as an MCP tool
• API Proxy: Acts as a bridge between MCP clients and the Perplexica search endpoint
• Parameter Passthrough: Forwards all search parameters (focus modes, models, etc.) to the Perplexica API
• MCP Protocol Compliance: Implements the Model Context Protocol for seamless integration with AI assistants

Installation

To use the Perplexica MCP Server, you'll need to have Python 3.12 or later installed on your system.

1. Clone this repository:

git clone https://github.com/yourusername/perplexica-mcp.git
cd perplexica-mcp

2. Install the required dependencies:

pip install -e .

MCP Server Configuration

This server is designed to be used with MCP-compatible clients. Add the following configuration to your MCP client:

{
  "mcpServers": {
    "perplexica": {
      "command": "uv",
      "args": ["run", "/path/to/perplexica-mcp/perplexica_mcp_tool.py"],
      "env": {
        "PERPLEXICA_BACKEND_URL": "http://localhost:3000/api/search"
      }
    }
  }
}

Backend URL Configuration

The Perplexica MCP Server uses an environment variable to configure the backend URL. To set this up:

1. Create a .env file in the root of the project (if it doesn't already exist)
2. Add the PERPLEXICA_BACKEND_URL variable with your desired backend URL:

PERPLEXICA_BACKEND_URL=http://localhost:3000/api/search

The server will use this URL to communicate with the Perplexica backend. If the environment variable is not set, it will default to http://localhost:3000/api/search.

Usage

This MCP server provides a search tool that can be used by MCP clients to perform searches through Perplexica. The tool accepts the following parameters:

Search Tool Parameters

• query (required): The search query string
• focus_mode (required): The search focus mode
• chat_model (optional): Chat model configuration
• embedding_model (optional): Embedding model configuration
• optimization_mode (optional): Performance optimization setting
• history (optional): Conversation history
• system_instructions (optional): Custom AI guidance
• stream (optional): Whether to stream responses

Example Usage via MCP Client

When connected to an MCP client, you can use the search tool like this:

Search for "Python programming best practices" using webSearch focus mode

The MCP client will automatically invoke the search tool with the appropriate parameters.

Perplexica Integration

This MCP server acts as a proxy to the Perplexica search API. All search parameters and configurations are passed through to the underlying Perplexica service:

• Focus Modes: Supports all Perplexica focus modes (webSearch, academicSearch, writingAssistant, wolframAlphaSearch, youtubeSearch, redditSearch)
• Model Configuration: Passes through chat model and embedding model settings to Perplexica
• Search Options: Forwards optimization modes, conversation history, and system instructions

For detailed information about Perplexica's capabilities and features, please refer to the Perplexica documentation.

Contributing

Contributions are welcome! Please open an issue or submit a pull request.

License

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