import json
from fastmcp import Context
from datetime import datetime
from dateutil import parser
from mcp_server.mcp_instance import mcp
from mcp_server.utils.get_weather_forecast import get_activity_suggestions as get_suggestions
from mcp_server.utils.elicitation import elicit_trip_extension
from mcp_server.core.prompts.travel import get_itinerary_prompt, get_weather_based_activities_prompt
@mcp.tool(
name="cox_ai_itinerary",
description="generate itinerary for coxs bazar",
)
async def cox_ai_itinerary(ctx: Context, start_date: str, days: int, ) -> str:
"""
Full workflow: fetch daily temperatures + generate AI itinerary.
Uses the registered MCP prompt 'generate_itinerary' for consistency.
Args:
days: Number of days for the trip
start_date: Start date (e.g., "2025-01-15", "15 Jan 2025", "today")
Returns:
Formatted prompt for AI to generate detailed itinerary
"""
# Elicit trip extension if needed (minimum 2 days recommended)
try:
days, elicitation_note = await elicit_trip_extension(ctx, start_date, days, min_days=2)
except ValueError as e:
# User cancelled the trip extension
await ctx.error(f"Error: {str(e)}")
return str(e)
# Parse start date
try:
start_date = parser.parse(start_date)
except Exception:
start_date = datetime.today()
# Get weather forecast
read_weather_forecast = await ctx.read_resource(f"weather://coxsbazar/forecast/{start_date.strftime('%Y-%m-%d')}/{days}")
weather_data = json.loads(read_weather_forecast[0].content)
# Generate base itinerary prompt
base_prompt = await get_itinerary_prompt(days, start_date)
# Generate weather-based activities prompt
weather_prompt = await get_weather_based_activities_prompt(weather_data)
# Format output
output = f"""# Cox's Bazar Itinerary Planning
## Trip Details
- **Location:** {weather_data['location']}
- **Start Date:** {weather_data['start_date']}
- **Duration:** {days} day(s)
- **Timezone:** {weather_data['timezone']}
## Weather Forecast
"""
# Add detailed forecast
for day in weather_data['forecast']:
output += f"""### Day {day['day']} - {day['date']}
- **Weather:** {day['weather']}
- **Temperature:** {day['temp_min']}°C - {day['temp_max']}°C (Average: {day['temp_avg']}°C)
- **Precipitation:** {day['precipitation']}mm
- **Wind Speed:** {day['windspeed']} km/h
- **Sunrise:** {day['sunrise']} | **Sunset:** {day['sunset']}
**Activity Suggestions:**
"""
# Get activity suggestions for different times
temp_avg = day['temp_avg']
morning_activities = get_suggestions(temp_avg - 2, "morning")
afternoon_activities = get_suggestions(temp_avg, "afternoon")
evening_activities = get_suggestions(temp_avg, "evening")
output += f"""
- **Morning:** {', '.join(morning_activities[:2])}
- **Afternoon:** {', '.join(afternoon_activities[:2])}
- **Evening:** {', '.join(evening_activities[:2])}
{elicitation_note}
"""
output += f"""
---
## AI Itinerary Generation Prompt
{base_prompt}
---
## Weather-Based Activities Prompt
{weather_prompt}
---
**Note:** Use the above prompts with an AI assistant to generate a detailed, personalized itinerary based on the weather forecast and your preferences.
"""
return output
@mcp.tool(
name="get_activity_suggestions",
description="suggest activities based on temperature and time of day",
)
async def get_activity_suggestions(temperature: float, time_of_day: str = "afternoon") -> list[str]:
"""
Suggest activities based on temperature and time of day.
Args:
temperature: Temperature in Celsius
time_of_day: "morning", "afternoon", or "evening"
Returns:
List of suggested activities
"""
return get_suggestions(temperature, time_of_day)
