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Perplexica Mcp Server

Created By
thetom427 months ago
A Model Context Protocol (MCP) server that provides search functionality using Perplexica's AI-powered search engine. Features - Search Tool: AI-powered web search with multiple focus modes - Multiple Transport Support: stdio, SSE, and Streamable HTTP transports - FastMCP Integration: Built using FastMCP for robust MCP protocol compliance - Unified Architecture: Single server implementation supporting all transport modes - Production Ready: Docker support with security best practices
Overview

what is Perplexica MCP Server?

Perplexica MCP Server is a Model Context Protocol (MCP) server that provides advanced search functionality using Perplexica's AI-powered search engine.

how to use Perplexica MCP Server?

To use the Perplexica MCP Server, install it via PyPI or from source, configure your MCP clients to connect to the server, and choose your desired transport mode (stdio, SSE, or HTTP).

key features of Perplexica MCP Server?

  • AI-powered web search with multiple focus modes
  • Support for stdio, SSE, and Streamable HTTP transports
  • Built using FastMCP for robust protocol compliance
  • Unified architecture for all transport modes
  • Docker support with security best practices

use cases of Perplexica MCP Server?

  1. Integrating AI-powered search capabilities into applications
  2. Real-time data retrieval for web-based applications
  3. Enhancing user experience with intelligent search functionalities

FAQ from Perplexica MCP Server?

  • What transport modes does the server support?

The server supports stdio, SSE, and Streamable HTTP transports.

  • Is there Docker support for deployment?

Yes, the server includes Docker support for containerized deployments.

  • How can I troubleshoot connection issues?

Ensure that the server is running, check the configured URLs, and verify that environment variables are set correctly.

Server Config

{
  "mcpServers": {
    "perplexica": {
      "command": "uvx",
      "args": [
        "perplexica-mcp",
        "stdio"
      ],
      "env": {
        "PERPLEXICA_BACKEND_URL": "http://localhost:3000/api/search"
      }
    }
  }
}
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