travel-mcp-server

get_weather

Retrieve day-by-day weather forecasts for any destination across a specified date range to plan trips accordingly.

Instructions

Get day-by-day weather forecast for a destination over a date range.

Args: destination: City name (e.g. "Tokyo", "Bali", "Sydney") date_from: Start date in YYYY-MM-DD format date_to: End date in YYYY-MM-DD format

Input Schema

TableJSON Schema

Name	Required	Description	Default
`destination`	Yes
`date_from`	Yes
`date_to`	Yes

Implementation Reference

src/travel_mcp/tools/weather.py:4-8 (handler)

Helper function get_forecast() that delegates to mock data query_forecast(). This is the business logic handler for the get_weather tool.

def get_forecast(destination: str, date_from: str, date_to: str) -> list[dict]:
    results = query_forecast(destination, date_from, date_to)
    if not results:
        return [{"message": f"Could not retrieve weather for '{destination}'. Check that dates are in YYYY-MM-DD format."}]
    return results

src/travel_mcp/server.py:62-76 (schema)

MCP tool definition for get_weather with type hints (params: destination, date_from, date_to) and docstring. This is the registration/schema of the tool.

@mcp.tool()
def get_weather(
    destination: str,
    date_from: str,
    date_to: str,
) -> list:
    """
    Get day-by-day weather forecast for a destination over a date range.

    Args:
        destination: City name (e.g. "Tokyo", "Bali", "Sydney")
        date_from: Start date in YYYY-MM-DD format
        date_to: End date in YYYY-MM-DD format
    """
    return weather.get_forecast(destination, date_from, date_to)

src/travel_mcp/server.py:191-195 (registration)

HTTP API route registration for POST /api/tools/get_weather wrapping the handler.

@mcp.custom_route("/api/tools/get_weather", methods=["POST"])
async def api_get_weather(request: Request) -> JSONResponse:
    body = await request.json()
    result = weather.get_forecast(body["destination"], body["date_from"], body["date_to"])
    return JSONResponse(result)

src/travel_mcp/mock_data/weather.py:140-177 (helper)

query_forecast() generates day-by-day weather from monthly averages. Core data logic with date iteration and daily variation.

def query_forecast(destination: str, date_from: str, date_to: str) -> list[dict]:
    city = destination.strip().lower()
    monthly = _MONTHLY.get(city)
    if not monthly:
        for key in _MONTHLY:
            if key in city or city in key:
                monthly = _MONTHLY[key]
                break
    if not monthly:
        monthly = _DEFAULT_WEATHER

    try:
        start = datetime.strptime(date_from, "%Y-%m-%d")
        end = datetime.strptime(date_to, "%Y-%m-%d")
    except ValueError:
        return []

    forecast = []
    current = start
    while current <= end:
        month_data = monthly[current.month - 1]
        # Add slight daily variation
        day_offset = (current - start).days
        high_var = (day_offset % 3) - 1  # -1, 0, +1 cycling
        forecast.append({
            "date": current.strftime("%Y-%m-%d"),
            "day_of_week": current.strftime("%A"),
            "high_celsius": month_data["avg_high"] + high_var,
            "low_celsius": month_data["avg_low"] + high_var,
            "high_fahrenheit": round((month_data["avg_high"] + high_var) * 9 / 5 + 32),
            "low_fahrenheit": round((month_data["avg_low"] + high_var) * 9 / 5 + 32),
            "condition": month_data["condition"],
            "humidity_pct": month_data["humidity"],
            "rain_chance_pct": month_data["rain_chance"],
        })
        current += timedelta(days=1)

    return forecast

src/travel_mcp/mock_data/weather.py:5-132 (helper)

Monthly climate data dictionary (_MONTHLY) for cities like Tokyo, Paris, London, Barcelona, Bali, Sydney, Rome, Amsterdam, Dubai.

_MONTHLY: dict[str, list[dict]] = {
    "tokyo": [
        {"month": 1,  "avg_high": 10, "avg_low": 2,  "condition": "Cold & Sunny",          "humidity": 52, "rain_chance": 20},
        {"month": 2,  "avg_high": 12, "avg_low": 3,  "condition": "Cold & Clear",           "humidity": 55, "rain_chance": 22},
        {"month": 3,  "avg_high": 15, "avg_low": 7,  "condition": "Mild, Cherry Blossoms",  "humidity": 60, "rain_chance": 30},
        {"month": 4,  "avg_high": 20, "avg_low": 12, "condition": "Warm & Pleasant",        "humidity": 65, "rain_chance": 35},
        {"month": 5,  "avg_high": 25, "avg_low": 17, "condition": "Warm",                   "humidity": 70, "rain_chance": 38},
        {"month": 6,  "avg_high": 28, "avg_low": 21, "condition": "Rainy Season",           "humidity": 80, "rain_chance": 55},
        {"month": 7,  "avg_high": 32, "avg_low": 25, "condition": "Hot & Humid",            "humidity": 85, "rain_chance": 40},
        {"month": 8,  "avg_high": 33, "avg_low": 26, "condition": "Hot & Humid",            "humidity": 85, "rain_chance": 35},
        {"month": 9,  "avg_high": 29, "avg_low": 22, "condition": "Warm, Typhoon Risk",     "humidity": 75, "rain_chance": 45},
        {"month": 10, "avg_high": 23, "avg_low": 16, "condition": "Pleasant Autumn",        "humidity": 65, "rain_chance": 30},
        {"month": 11, "avg_high": 17, "avg_low": 9,  "condition": "Cool & Clear",           "humidity": 60, "rain_chance": 25},
        {"month": 12, "avg_high": 12, "avg_low": 4,  "condition": "Cold & Clear",           "humidity": 55, "rain_chance": 18},
    ],
    "paris": [
        {"month": 1,  "avg_high": 7,  "avg_low": 3,  "condition": "Cold & Overcast",  "humidity": 82, "rain_chance": 45},
        {"month": 2,  "avg_high": 8,  "avg_low": 3,  "condition": "Cold & Cloudy",    "humidity": 78, "rain_chance": 40},
        {"month": 3,  "avg_high": 12, "avg_low": 6,  "condition": "Cool & Variable",  "humidity": 75, "rain_chance": 38},
        {"month": 4,  "avg_high": 16, "avg_low": 9,  "condition": "Mild & Showery",   "humidity": 72, "rain_chance": 40},
        {"month": 5,  "avg_high": 20, "avg_low": 13, "condition": "Warm & Sunny",     "humidity": 68, "rain_chance": 35},
        {"month": 6,  "avg_high": 24, "avg_low": 16, "condition": "Warm & Sunny",     "humidity": 65, "rain_chance": 30},
        {"month": 7,  "avg_high": 26, "avg_low": 18, "condition": "Hot & Sunny",      "humidity": 62, "rain_chance": 25},
        {"month": 8,  "avg_high": 26, "avg_low": 18, "condition": "Hot & Sunny",      "humidity": 63, "rain_chance": 25},
        {"month": 9,  "avg_high": 22, "avg_low": 14, "condition": "Pleasant",         "humidity": 68, "rain_chance": 30},
        {"month": 10, "avg_high": 16, "avg_low": 10, "condition": "Cool & Rainy",     "humidity": 78, "rain_chance": 42},
        {"month": 11, "avg_high": 10, "avg_low": 6,  "condition": "Cold & Overcast",  "humidity": 83, "rain_chance": 48},
        {"month": 12, "avg_high": 7,  "avg_low": 3,  "condition": "Cold & Grey",      "humidity": 84, "rain_chance": 50},
    ],
    "london": [
        {"month": 1,  "avg_high": 8,  "avg_low": 3,  "condition": "Cold & Overcast",  "humidity": 80, "rain_chance": 50},
        {"month": 2,  "avg_high": 9,  "avg_low": 3,  "condition": "Cold & Grey",      "humidity": 77, "rain_chance": 45},
        {"month": 3,  "avg_high": 12, "avg_low": 5,  "condition": "Cool & Changeable","humidity": 74, "rain_chance": 40},
        {"month": 4,  "avg_high": 15, "avg_low": 7,  "condition": "Mild & Showery",   "humidity": 70, "rain_chance": 42},
        {"month": 5,  "avg_high": 19, "avg_low": 10, "condition": "Mild & Sunny",     "humidity": 65, "rain_chance": 35},
        {"month": 6,  "avg_high": 22, "avg_low": 13, "condition": "Warm & Sunny",     "humidity": 63, "rain_chance": 30},
        {"month": 7,  "avg_high": 24, "avg_low": 15, "condition": "Warm & Sunny",     "humidity": 60, "rain_chance": 28},
        {"month": 8,  "avg_high": 24, "avg_low": 15, "condition": "Warm & Sunny",     "humidity": 62, "rain_chance": 30},
        {"month": 9,  "avg_high": 20, "avg_low": 12, "condition": "Pleasant",         "humidity": 68, "rain_chance": 35},
        {"month": 10, "avg_high": 15, "avg_low": 8,  "condition": "Cool & Rainy",     "humidity": 76, "rain_chance": 48},
        {"month": 11, "avg_high": 11, "avg_low": 5,  "condition": "Cold & Wet",       "humidity": 82, "rain_chance": 52},
        {"month": 12, "avg_high": 8,  "avg_low": 3,  "condition": "Cold & Overcast",  "humidity": 83, "rain_chance": 55},
    ],
    "barcelona": [
        {"month": 1,  "avg_high": 13, "avg_low": 6,  "condition": "Cool & Sunny",     "humidity": 65, "rain_chance": 25},
        {"month": 2,  "avg_high": 14, "avg_low": 7,  "condition": "Cool & Sunny",     "humidity": 63, "rain_chance": 22},
        {"month": 3,  "avg_high": 16, "avg_low": 9,  "condition": "Mild & Variable",  "humidity": 65, "rain_chance": 30},
        {"month": 4,  "avg_high": 18, "avg_low": 11, "condition": "Mild & Pleasant",  "humidity": 62, "rain_chance": 32},
        {"month": 5,  "avg_high": 22, "avg_low": 15, "condition": "Warm & Sunny",     "humidity": 65, "rain_chance": 28},
        {"month": 6,  "avg_high": 26, "avg_low": 19, "condition": "Hot & Sunny",      "humidity": 65, "rain_chance": 20},
        {"month": 7,  "avg_high": 29, "avg_low": 22, "condition": "Very Hot & Sunny", "humidity": 65, "rain_chance": 10},
        {"month": 8,  "avg_high": 29, "avg_low": 22, "condition": "Very Hot & Sunny", "humidity": 68, "rain_chance": 15},
        {"month": 9,  "avg_high": 26, "avg_low": 19, "condition": "Warm & Sunny",     "humidity": 68, "rain_chance": 25},
        {"month": 10, "avg_high": 21, "avg_low": 15, "condition": "Mild & Sunny",     "humidity": 68, "rain_chance": 35},
        {"month": 11, "avg_high": 17, "avg_low": 11, "condition": "Cool & Variable",  "humidity": 68, "rain_chance": 32},
        {"month": 12, "avg_high": 14, "avg_low": 8,  "condition": "Cool & Sunny",     "humidity": 66, "rain_chance": 25},
    ],
    "bali": [
        {"month": 1,  "avg_high": 30, "avg_low": 24, "condition": "Wet Season",       "humidity": 85, "rain_chance": 70},
        {"month": 2,  "avg_high": 30, "avg_low": 24, "condition": "Wet Season",       "humidity": 85, "rain_chance": 72},
        {"month": 3,  "avg_high": 31, "avg_low": 24, "condition": "Wet Season",       "humidity": 83, "rain_chance": 65},
        {"month": 4,  "avg_high": 31, "avg_low": 24, "condition": "Transitional",     "humidity": 80, "rain_chance": 50},
        {"month": 5,  "avg_high": 31, "avg_low": 23, "condition": "Dry Season Start", "humidity": 75, "rain_chance": 35},
        {"month": 6,  "avg_high": 30, "avg_low": 22, "condition": "Dry & Breezy",     "humidity": 70, "rain_chance": 20},
        {"month": 7,  "avg_high": 29, "avg_low": 21, "condition": "Peak Dry Season",  "humidity": 68, "rain_chance": 12},
        {"month": 8,  "avg_high": 29, "avg_low": 21, "condition": "Peak Dry Season",  "humidity": 68, "rain_chance": 10},
        {"month": 9,  "avg_high": 30, "avg_low": 22, "condition": "Dry & Sunny",      "humidity": 70, "rain_chance": 18},
        {"month": 10, "avg_high": 31, "avg_low": 23, "condition": "Transitional",     "humidity": 75, "rain_chance": 35},
        {"month": 11, "avg_high": 31, "avg_low": 24, "condition": "Wet Season Start", "humidity": 80, "rain_chance": 55},
        {"month": 12, "avg_high": 30, "avg_low": 24, "condition": "Wet Season",       "humidity": 85, "rain_chance": 68},
    ],
    "sydney": [
        {"month": 1,  "avg_high": 26, "avg_low": 19, "condition": "Hot & Sunny",      "humidity": 65, "rain_chance": 35},
        {"month": 2,  "avg_high": 26, "avg_low": 19, "condition": "Hot & Humid",      "humidity": 68, "rain_chance": 38},
        {"month": 3,  "avg_high": 24, "avg_low": 18, "condition": "Warm & Changeable","humidity": 68, "rain_chance": 40},
        {"month": 4,  "avg_high": 22, "avg_low": 15, "condition": "Mild & Sunny",     "humidity": 65, "rain_chance": 32},
        {"month": 5,  "avg_high": 19, "avg_low": 12, "condition": "Cool & Sunny",     "humidity": 62, "rain_chance": 28},
        {"month": 6,  "avg_high": 17, "avg_low": 9,  "condition": "Cool & Rainy",     "humidity": 65, "rain_chance": 35},
        {"month": 7,  "avg_high": 16, "avg_low": 8,  "condition": "Cold & Clear",     "humidity": 62, "rain_chance": 28},
        {"month": 8,  "avg_high": 18, "avg_low": 9,  "condition": "Cool & Sunny",     "humidity": 60, "rain_chance": 25},
        {"month": 9,  "avg_high": 20, "avg_low": 11, "condition": "Warm & Sunny",     "humidity": 62, "rain_chance": 30},
        {"month": 10, "avg_high": 22, "avg_low": 14, "condition": "Warm & Pleasant",  "humidity": 65, "rain_chance": 35},
        {"month": 11, "avg_high": 24, "avg_low": 16, "condition": "Warm & Sunny",     "humidity": 65, "rain_chance": 35},
        {"month": 12, "avg_high": 26, "avg_low": 18, "condition": "Hot & Sunny",      "humidity": 65, "rain_chance": 35},
    ],
    "rome": [
        {"month": 1,  "avg_high": 12, "avg_low": 4,  "condition": "Cool & Rainy",     "humidity": 72, "rain_chance": 40},
        {"month": 2,  "avg_high": 13, "avg_low": 5,  "condition": "Cool & Variable",  "humidity": 68, "rain_chance": 35},
        {"month": 3,  "avg_high": 16, "avg_low": 7,  "condition": "Mild & Sunny",     "humidity": 65, "rain_chance": 32},
        {"month": 4,  "avg_high": 19, "avg_low": 10, "condition": "Warm & Pleasant",  "humidity": 62, "rain_chance": 28},
        {"month": 5,  "avg_high": 24, "avg_low": 14, "condition": "Warm & Sunny",     "humidity": 60, "rain_chance": 20},
        {"month": 6,  "avg_high": 28, "avg_low": 18, "condition": "Hot & Sunny",      "humidity": 55, "rain_chance": 12},
        {"month": 7,  "avg_high": 31, "avg_low": 20, "condition": "Very Hot & Sunny", "humidity": 48, "rain_chance": 8},
        {"month": 8,  "avg_high": 31, "avg_low": 20, "condition": "Very Hot & Sunny", "humidity": 50, "rain_chance": 10},
        {"month": 9,  "avg_high": 27, "avg_low": 17, "condition": "Warm & Pleasant",  "humidity": 58, "rain_chance": 18},
        {"month": 10, "avg_high": 22, "avg_low": 13, "condition": "Mild & Variable",  "humidity": 68, "rain_chance": 32},
        {"month": 11, "avg_high": 16, "avg_low": 9,  "condition": "Cool & Rainy",     "humidity": 74, "rain_chance": 42},
        {"month": 12, "avg_high": 13, "avg_low": 5,  "condition": "Cool & Rainy",     "humidity": 74, "rain_chance": 42},
    ],
    "amsterdam": [
        {"month": 1,  "avg_high": 6,  "avg_low": 1,  "condition": "Cold & Overcast",  "humidity": 86, "rain_chance": 55},
        {"month": 2,  "avg_high": 7,  "avg_low": 1,  "condition": "Cold & Cloudy",    "humidity": 82, "rain_chance": 50},
        {"month": 3,  "avg_high": 10, "avg_low": 4,  "condition": "Cool & Changeable","humidity": 78, "rain_chance": 45},
        {"month": 4,  "avg_high": 14, "avg_low": 6,  "condition": "Mild & Variable",  "humidity": 74, "rain_chance": 40},
        {"month": 5,  "avg_high": 18, "avg_low": 10, "condition": "Warm & Sunny",     "humidity": 70, "rain_chance": 35},
        {"month": 6,  "avg_high": 21, "avg_low": 13, "condition": "Warm & Pleasant",  "humidity": 70, "rain_chance": 32},
        {"month": 7,  "avg_high": 23, "avg_low": 15, "condition": "Warm & Sunny",     "humidity": 70, "rain_chance": 30},
        {"month": 8,  "avg_high": 23, "avg_low": 14, "condition": "Warm & Sunny",     "humidity": 72, "rain_chance": 32},
        {"month": 9,  "avg_high": 19, "avg_low": 11, "condition": "Mild & Sunny",     "humidity": 76, "rain_chance": 38},
        {"month": 10, "avg_high": 14, "avg_low": 8,  "condition": "Cool & Rainy",     "humidity": 82, "rain_chance": 50},
        {"month": 11, "avg_high": 9,  "avg_low": 4,  "condition": "Cold & Overcast",  "humidity": 86, "rain_chance": 55},
        {"month": 12, "avg_high": 7,  "avg_low": 2,  "condition": "Cold & Overcast",  "humidity": 87, "rain_chance": 58},
    ],
    "dubai": [
        {"month": 1,  "avg_high": 24, "avg_low": 14, "condition": "Warm & Sunny",     "humidity": 60, "rain_chance": 5},
        {"month": 2,  "avg_high": 26, "avg_low": 15, "condition": "Warm & Sunny",     "humidity": 58, "rain_chance": 5},
        {"month": 3,  "avg_high": 30, "avg_low": 19, "condition": "Hot & Sunny",      "humidity": 55, "rain_chance": 5},
        {"month": 4,  "avg_high": 35, "avg_low": 22, "condition": "Very Hot & Sunny", "humidity": 50, "rain_chance": 3},
        {"month": 5,  "avg_high": 40, "avg_low": 27, "condition": "Extremely Hot",    "humidity": 45, "rain_chance": 1},
        {"month": 6,  "avg_high": 42, "avg_low": 29, "condition": "Extremely Hot",    "humidity": 55, "rain_chance": 0},
        {"month": 7,  "avg_high": 41, "avg_low": 30, "condition": "Extremely Hot",    "humidity": 60, "rain_chance": 0},
        {"month": 8,  "avg_high": 41, "avg_low": 30, "condition": "Extremely Hot",    "humidity": 62, "rain_chance": 0},
        {"month": 9,  "avg_high": 38, "avg_low": 27, "condition": "Very Hot & Humid", "humidity": 65, "rain_chance": 0},
        {"month": 10, "avg_high": 34, "avg_low": 23, "condition": "Hot & Sunny",      "humidity": 60, "rain_chance": 1},
        {"month": 11, "avg_high": 29, "avg_low": 19, "condition": "Warm & Sunny",     "humidity": 58, "rain_chance": 3},
        {"month": 12, "avg_high": 25, "avg_low": 15, "condition": "Warm & Sunny",     "humidity": 60, "rain_chance": 5},
    ],
}

Tool Definition Quality

A4.1/5.0

Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description mentions 'day-by-day' forecast, indicating granularity, but does not disclose limitations like maximum date range, data sources, update frequency, or output format. Without annotations, more behavioral context would be beneficial.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise with a brief introductory sentence followed by a clear Args section. Every sentence adds value, with no fluff or repetition. It is well-structured for quick understanding.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the absence of an output schema and annotations, the description covers basic input guidance but does not explain the return value structure (e.g., daily forecasts with details). Additional context like unit system or location validation would improve completeness.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

All three parameters have no schema descriptions (0% coverage). The description compensates by providing examples for destination (e.g., 'Tokyo') and specifying date format (YYYY-MM-DD) for both date_from and date_to. However, it does not mention any constraints like valid date ranges or supported cities.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states 'Get day-by-day weather forecast for a destination over a date range.' It uses a specific verb 'Get' and clearly identifies the resource (weather forecast) and scope (destination, date range). It is distinct from sibling tools like search_flights or search_hotels.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for weather forecasts but does not explicitly state when to use this tool versus alternatives. No when-not or alternative tool references are provided, but the purpose is clear enough from the context of sibling tool names.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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