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Perplexica Mcp Server

Created By
thetom425 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
Content

Perplexica MCP Server

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

Installation

# Install directly from PyPI
pip install perplexica-mcp

# Or using uvx for isolated execution
uvx perplexica-mcp --help

From Source

# Clone the repository
git clone https://github.com/thetom42/perplexica-mcp.git
cd perplexica-mcp

# Install dependencies
uv sync

MCP Client Configuration

To use this server with MCP clients, you need to configure the client to connect to the Perplexica MCP server. Below are configuration examples for popular MCP clients.

Claude Desktop

Add the following to your Claude Desktop configuration file:

Location: ~/Library/Application Support/Claude/claude_desktop_config.json (macOS) or %APPDATA%\Claude\claude_desktop_config.json (Windows)

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

Alternative (from source):

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

SSE Transport

For SSE transport, first start the server:

uv run src/perplexica_mcp.py sse

Then configure Claude Desktop:

{
  "mcpServers": {
    "perplexica": {
      "url": "http://localhost:3001/sse"
    }
  }
}

Cursor IDE

Add to your Cursor MCP configuration:

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

Alternative (from source):

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

Generic MCP Client Configuration

For any MCP client supporting stdio transport:

# Command to run the server (PyPI installation)
uvx perplexica-mcp stdio

# Command to run the server (from source)
uv run /path/to/perplexica-mcp/src/perplexica_mcp.py stdio

# Environment variables
PERPLEXICA_BACKEND_URL=http://localhost:3000/api/search

For HTTP/SSE transport clients:

# Start the server (PyPI installation)
uvx perplexica-mcp sse  # or 'http'

# Start the server (from source)
uv run /path/to/perplexica-mcp/src/perplexica_mcp.py sse  # or 'http'

# Connect to endpoints
SSE: http://localhost:3001/sse
HTTP: http://localhost:3002/mcp/

Configuration Notes

  1. Path Configuration: Replace /path/to/perplexica-mcp/ with the actual path to your installation
  2. Perplexica URL: Ensure PERPLEXICA_BACKEND_URL points to your running Perplexica instance
  3. Transport Selection:
    • Use stdio for most MCP clients (Claude Desktop, Cursor)
    • Use SSE for web-based clients or real-time applications
    • Use HTTP for REST API integrations
  4. Dependencies: Ensure uvx is installed and available in your PATH (or uv for source installations)

Troubleshooting

  • Server not starting: Check that uvx (or uv for source) is installed and the path is correct
  • Connection refused: Verify Perplexica is running and accessible at the configured URL
  • Permission errors: Ensure the MCP client has permission to execute the server command
  • Environment variables: Check that PERPLEXICA_BACKEND_URL is properly set

Server Configuration

Create a .env file in the project root with your Perplexica configuration:

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

Usage

The server supports three transport modes:

1. Stdio Transport

# PyPI installation
uvx perplexica-mcp stdio

# From source
uv run src/perplexica_mcp.py stdio

2. SSE Transport

# PyPI installation
uvx perplexica-mcp sse [host] [port]

# From source
uv run src/perplexica_mcp.py sse [host] [port]
# Default: localhost:3001, endpoint: /sse

3. Streamable HTTP Transport

# PyPI installation
uvx perplexica-mcp http [host] [port]

# From source
uv run src/perplexica_mcp.py http [host] [port]
# Default: localhost:3002, endpoint: /mcp

Docker Deployment

The server includes Docker support with multiple transport configurations for containerized deployments.

Prerequisites

  • Docker and Docker Compose installed
  • External Docker network named backend (for integration with Perplexica)

Create External Network

docker network create backend

Build and Run

Option 1: HTTP Transport (Streamable HTTP)

# Build and run with HTTP transport
docker-compose up -d

# Or build first, then run
docker-compose build
docker-compose up -d

Option 2: SSE Transport (Server-Sent Events)

# Build and run with SSE transport
docker-compose -f docker-compose-sse.yml up -d

# Or build first, then run
docker-compose -f docker-compose-sse.yml build
docker-compose -f docker-compose-sse.yml up -d

Environment Configuration

Both Docker configurations support environment variables:

# Create .env file for Docker
cat > .env << EOF
PERPLEXICA_BACKEND_URL=http://perplexica-app:3000/api/search
EOF

# Uncomment env_file in docker-compose.yml to use .env file

Or set environment variables directly in the compose file:

environment:
  - PERPLEXICA_BACKEND_URL=http://your-perplexica-host:3000/api/search

Container Details

TransportContainer NamePortEndpointHealth Check
HTTPperplexica-mcp-http3001/mcp/MCP initialize request
SSEperplexica-mcp-sse3001/sseSSE endpoint check

Health Monitoring

Both containers include health checks:

# Check container health
docker ps
docker-compose ps

# View health check logs
docker logs perplexica-mcp-http
docker logs perplexica-mcp-sse

Integration with Perplexica

The Docker setup assumes Perplexica is running in the same Docker network:

# Example Perplexica service in the same compose file
services:
  perplexica-app:
    # ... your Perplexica configuration
    networks:
      - backend
  
  perplexica-mcp:
    # ... MCP server configuration
    environment:
      - PERPLEXICA_BACKEND_URL=http://perplexica-app:3000/api/search
    networks:
      - backend

Production Considerations

  • Both containers use restart: unless-stopped for reliability
  • Health checks ensure service availability
  • External network allows integration with existing Perplexica deployments
  • Security best practices implemented in Dockerfile

Available Tools

Performs AI-powered web search using Perplexica.

Parameters:

  • query (string, required): Search query
  • focus_mode (string, required): One of 'webSearch', 'academicSearch', 'writingAssistant', 'wolframAlphaSearch', 'youtubeSearch', 'redditSearch'
  • chat_model (string, optional): Chat model configuration
  • embedding_model (string, optional): Embedding model configuration
  • optimization_mode (string, optional): 'speed' or 'balanced'
  • history (array, optional): Conversation history
  • system_instructions (string, optional): Custom instructions
  • stream (boolean, optional): Whether to stream responses

Testing

Run the comprehensive test suite to verify all transports:

uv run src/test_transports.py

This will test:

  • ✓ Stdio transport with MCP protocol handshake
  • ✓ HTTP transport with Streamable HTTP compliance
  • ✓ SSE transport endpoint accessibility

Transport Details

Stdio Transport

  • Uses FastMCP's built-in stdio server
  • Supports full MCP protocol including initialization and tool listing
  • Ideal for MCP client integration

SSE Transport

  • Server-Sent Events for real-time communication
  • Endpoint: http://host:port/sse
  • Includes periodic ping messages for connection health

Streamable HTTP Transport

  • Compliant with MCP Streamable HTTP specification
  • Endpoint: http://host:port/mcp
  • Returns 307 redirect to /mcp/ as per protocol
  • Uses StreamableHTTPSessionManager for proper session handling

Development

The server is built using:

  • FastMCP: Modern MCP server framework with built-in transport support
  • Uvicorn: ASGI server for SSE and HTTP transports
  • httpx: HTTP client for Perplexica API communication
  • python-dotenv: Environment variable management

Architecture

┌─────────────────┐    ┌──────────────────┐    ┌─────────────────┐
│   MCP Client    │◄──►│ Perplexica MCP   │◄──►│   Perplexica    │
│                 │    │     Server       │    │   Search API    │
│  (stdio/SSE/    │    │   (FastMCP)      │    │                 │
│   HTTP)         │    │                  │    │                 │
└─────────────────┘    └──────────────────┘    └─────────────────┘
                       ┌──────────────┐
                       │   FastMCP    │
                       │  Framework   │
                       │ ┌──────────┐ │
                       │ │  stdio   │ │
                       │ │   SSE    │ │
                       │ │  HTTP    │ │
                       │ └──────────┘ │
                       └──────────────┘

License

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

Contributing

  1. Fork the repository
  2. Create a feature branch
  3. Make your changes
  4. Add tests if applicable
  5. Submit a pull request

Support

For issues and questions:

  • Check the troubleshooting section
  • Review the Perplexica documentation
  • Open an issue on GitHub

Server Config

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