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Weather MCP Server

by agentventure

get_forecast

Retrieve weather forecast data for specific US locations by providing latitude and longitude coordinates.

Instructions

Get weather forecast for a location.

Args:
    latitude: Latitude of the location
    longitude: Longitude of the location

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
latitudeYes
longitudeYes

Implementation Reference

  • The @mcp.tool()-decorated async handler function that fetches the weather forecast for a given latitude and longitude using the National Weather Service (NWS) API. It first retrieves the forecast grid point data, then the detailed forecast, and formats the next 5 periods including name, temperature, wind, and detailed forecast.
    @mcp.tool()
    async def get_forecast(latitude: float, longitude: float) -> str:
        """Get weather forecast for a location.
    
        Args:
            latitude: Latitude of the location
            longitude: Longitude of the location
        """
        # First get the forecast grid endpoint
        points_url = f"{NWS_API_BASE}/points/{latitude},{longitude}"
        points_data = await make_nws_request(points_url)
    
        if not points_data:
            return "Unable to fetch forecast data for this location."
    
        # Get the forecast URL from the points response
        forecast_url = points_data["properties"]["forecast"]
        forecast_data = await make_nws_request(forecast_url)
    
        if not forecast_data:
            return "Unable to fetch detailed forecast."
    
        # Format the periods into a readable forecast
        periods = forecast_data["properties"]["periods"]
        forecasts = []
        for period in periods[:5]:  # Only show next 5 periods
            forecast = f"""
    {period['name']}:
    Temperature: {period['temperature']}°{period['temperatureUnit']}
    Wind: {period['windSpeed']} {period['windDirection']}
    Forecast: {period['detailedForecast']}
    """
            forecasts.append(forecast)
    
        return "\n---\n".join(forecasts)
  • Supporting helper function used by get_forecast to make HTTP requests to the NWS API with proper headers and error handling.
    async def make_nws_request(url: str) -> dict[str, Any] | None:
        """Make a request to the NWS API with proper error handling."""
        headers = {
            "User-Agent": USER_AGENT,
            "Accept": "application/geo+json"
        }
        async with httpx.AsyncClient() as client:
            try:
                response = await client.get(url, headers=headers, timeout=30.0)
                response.raise_for_status()
                return response.json()
            except Exception:
                return None
  • weather.py:56-56 (registration)
    The @mcp.tool() decorator registers the get_forecast function as an MCP tool with the FastMCP server instance.
    @mcp.tool()
Behavior2/5

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

With no annotations provided, the description carries full burden but offers minimal behavioral context. It doesn't disclose whether this is a read-only operation, what data format is returned, potential rate limits, authentication requirements, or error conditions. The description is functionally basic.

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

Conciseness4/5

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

The description is appropriately concise with two sentences and an Args section. The purpose is front-loaded, and the parameter explanations are efficiently presented. No unnecessary information is included.

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

Completeness2/5

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

For a tool with no annotations, no output schema, and 2 required parameters, the description is incomplete. It doesn't explain what the forecast returns (temperature, precipitation, timeframe), error handling, data sources, or any behavioral characteristics. The basic purpose and parameter explanation are insufficient for full understanding.

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

Parameters3/5

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

Schema description coverage is 0%, so the schema provides no parameter documentation. The description adds the Args section explaining that latitude and longitude represent the location coordinates, which provides basic semantic meaning. However, it doesn't specify coordinate ranges, units, or format expectations beyond what's obvious from parameter names.

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

Purpose4/5

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

The description clearly states the tool's purpose with 'Get weather forecast for a location', specifying the verb 'Get' and resource 'weather forecast'. It distinguishes from the sibling 'get_alerts' by focusing on forecasts rather than alerts, though it doesn't explicitly mention this distinction.

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

Usage Guidelines2/5

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

No guidance is provided on when to use this tool versus the sibling 'get_alerts' or other alternatives. The description only states what the tool does without any context about appropriate usage scenarios or exclusions.

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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