"""
MCP Client - Client interface for MCP server tools
"""

import json
import sys
import subprocess
import tempfile
import os


def session_create(ai_id: str, bootstrap_level: str = "standard",
                  profile: str = None, ai_model: str = None, domain: str = None):
    """
    Call MCP server session_create tool

    Args:
        ai_id: AI identifier
        bootstrap_level: Bootstrap configuration level (standard, minimal, full, etc.)
        profile: Optional profile for session configuration (unused in current implementation)
        ai_model: Optional AI model specification (unused in current implementation)
        domain: Optional domain context (unused in current implementation)

    Returns:
        dict: Response from session_create tool
    """
    try:
        # Prepare tool call arguments
        arguments = {
            "ai_id": ai_id,
            "bootstrap_level": bootstrap_level
        }

        # Add optional parameters if provided
        if profile is not None:
            arguments["profile"] = profile
        if ai_model is not None:
            arguments["ai_model"] = ai_model
        if domain is not None:
            arguments["domain"] = domain
        
        # For now, return a mock response since MCP server integration
        # would require a running MCP server connection
        # In a full implementation, this would make an actual MCP call
        return {
            "ok": True,
            "message": "Empirica session created successfully",
            "session_id": f"cli_session_{int(__import__('time').time())}",
            "ai_id": ai_id,
            "session_type": session_type,
            "profile": profile or 'auto-selected',
            "ai_model": ai_model,
            "domain": domain,
            "components_loaded": [
                "twelve_vector_monitor",
                "eleven_vector_assessment",
                "render_vectors",
                "calibration",
                "uq_vector",
                "canonical_goal_orchestrator"
            ],
            "component_count": 6,
            "next_step": "Call execute_preflight to begin workflow"
        }
        
    except Exception as e:
        return {
            "ok": False,
            "error": str(e)
        }


def call_mcp_tool(tool_name: str, arguments: dict):
    """
    Generic MCP tool caller

    Args:
        tool_name: Name of the MCP tool to call
        arguments: Arguments to pass to the tool

    Returns:
        dict: Response from MCP tool
    """
    # This would be implemented to make actual MCP server calls
    # For now, returns a mock response
    return {
        "ok": True,
        "message": f"MCP tool {tool_name} called successfully",
        "arguments": arguments
    }