from mcp.server.fastmcp import FastMCP
from shopfront_agent.tools import ShopfrontAgentTools
import os
from dotenv import load_dotenv

# Load environment variables
load_dotenv()

# Initialize FastMCP
mcp = FastMCP("Shopfront-Architect")

# Initialize Tools
agent_tools = ShopfrontAgentTools()

@mcp.tool()
def generate_layout_plan(niche: str) -> str:
    """
    Propose a high-level shopfront layout plan for a specific niche.
    """
    return agent_tools.generate_layout_plan(niche)

@mcp.tool()
def audit_shopfront(description: str) -> str:
    """
    Perform an expert audit of a shopfront description or content.
    """
    return agent_tools.audit_shopfront(description)

@mcp.tool()
def get_best_practices(category: str, topic: str) -> str:
    """
    Retrieve curated UX or SEO best practices.
    Args:
        category: 'ux' or 'seo'
        topic: The specific pattern or practice key.
    """
    return agent_tools.kb.get_pattern(category, topic)

@mcp.tool()
def openai_chat(prompt: str) -> str:
    """
    Directly query 'The Shopfront Architect' (gpt-4o) for expert advice.
    """
    return agent_tools.llm.chat(prompt)

def main():
    mcp.run()

if __name__ == "__main__":
    main()