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Perplexica Mcp
What is Perplexica Mcp
Perplexica-MCP is a Model Context Protocol (MCP) server that leverages Perplexica’s AI-powered search engine to provide advanced search functionalities.
Use cases
Use cases include integrating with applications that require enhanced search functionalities, providing real-time search results, and supporting data-driven decision-making processes.
How to use
To use Perplexica-MCP, install it via PyPI with ‘pip install perplexica-mcp’ or clone the repository from GitHub. Configure your MCP client to connect to the server using the provided configuration examples.
Key features
Key features include AI-powered web search, support for multiple transport modes (stdio, SSE, Streamable HTTP), FastMCP integration for protocol compliance, a unified architecture for all transport modes, and production readiness with Docker support.
Where to use
Perplexica-MCP can be used in various fields that require advanced search capabilities, such as data analysis, research, and application development.
Clients Supporting MCP
The following are the main client software that supports the Model Context Protocol. Click the link to visit the official website for more information.
Overview
What is Perplexica Mcp
Perplexica-MCP is a Model Context Protocol (MCP) server that leverages Perplexica’s AI-powered search engine to provide advanced search functionalities.
Use cases
Use cases include integrating with applications that require enhanced search functionalities, providing real-time search results, and supporting data-driven decision-making processes.
How to use
To use Perplexica-MCP, install it via PyPI with ‘pip install perplexica-mcp’ or clone the repository from GitHub. Configure your MCP client to connect to the server using the provided configuration examples.
Key features
Key features include AI-powered web search, support for multiple transport modes (stdio, SSE, Streamable HTTP), FastMCP integration for protocol compliance, a unified architecture for all transport modes, and production readiness with Docker support.
Where to use
Perplexica-MCP can be used in various fields that require advanced search capabilities, such as data analysis, research, and application development.
Clients Supporting MCP
The following are the main client software that supports the Model Context Protocol. Click the link to visit the official website for more information.
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
From PyPI (Recommended)
# 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
Stdio Transport (Recommended)
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
- Path Configuration: Replace
/path/to/perplexica-mcp/
with the actual path to your installation - Perplexica URL: Ensure
PERPLEXICA_BACKEND_URL
points to your running Perplexica instance - 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
- Dependencies: Ensure
uvx
is installed and available in your PATH (oruv
for source installations)
Troubleshooting
- Server not starting: Check that
uvx
(oruv
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
Transport | Container Name | Port | Endpoint | Health Check |
---|---|---|---|---|
HTTP | perplexica-mcp-http |
3001 | /mcp/ |
MCP initialize request |
SSE | perplexica-mcp-sse |
3001 | /sse |
SSE 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
search
Performs AI-powered web search using Perplexica.
Parameters:
query
(string, required): Search queryfocus_mode
(string, required): One of ‘webSearch’, ‘academicSearch’, ‘writingAssistant’, ‘wolframAlphaSearch’, ‘youtubeSearch’, ‘redditSearch’chat_model
(string, optional): Chat model configurationembedding_model
(string, optional): Embedding model configurationoptimization_mode
(string, optional): ‘speed’ or ‘balanced’history
(array, optional): Conversation historysystem_instructions
(string, optional): Custom instructionsstream
(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
- Fork the repository
- Create a feature branch
- Make your changes
- Add tests if applicable
- Submit a pull request
Support
For issues and questions:
- Check the troubleshooting section
- Review the Perplexica documentation
- Open an issue on GitHub
DevTools Supporting MCP
The following are the main code editors that support the Model Context Protocol. Click the link to visit the official website for more information.