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Weather MCP Server

get_forecast

Retrieve weather forecasts for specific locations using latitude and longitude coordinates.

Instructions

Get weather forecast for a location

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
latitudeYesLatitude of the location
longitudeYesLongitude of the location

Implementation Reference

  • The main handler function that implements the logic for the 'get_forecast' tool. It fetches grid point data, then forecast data from the National Weather Service API, formats the periods, and returns a text response.
    async ({ latitude, longitude }) => {
      // Get grid point data
      const pointsUrl = `${NWS_API_BASE}/points/${latitude.toFixed(4)},${longitude.toFixed(4)}`;
      const pointsData = await makeNWSRequest<PointsResponse>(pointsUrl);
    
      if (!pointsData) {
        return {
          content: [
            {
              type: "text",
              text: `Failed to retrieve grid point data for coordinates: ${latitude}, ${longitude}. This location may not be supported by the NWS API (only US locations are supported).`,
            },
          ],
        };
      }
    
      const forecastUrl = pointsData.properties?.forecast;
      if (!forecastUrl) {
        return {
          content: [
            {
              type: "text",
              text: "Failed to get forecast URL from grid point data",
            },
          ],
        };
      }
    
      // Get forecast data
      const forecastData = await makeNWSRequest<ForecastResponse>(forecastUrl);
      if (!forecastData) {
        return {
          content: [
            {
              type: "text",
              text: "Failed to retrieve forecast data",
            },
          ],
        };
      }
    
      const periods = forecastData.properties?.periods || [];
      if (periods.length === 0) {
        return {
          content: [
            {
              type: "text",
              text: "No forecast periods available",
            },
          ],
        };
      }
    
      // Format forecast periods
      const formattedForecast = periods.map((period: ForecastPeriod) =>
        [
          `${period.name || "Unknown"}:`,
          `Temperature: ${period.temperature || "Unknown"}°${period.temperatureUnit || "F"}`,
          `Wind: ${period.windSpeed || "Unknown"} ${period.windDirection || ""}`,
          `${period.shortForecast || "No forecast available"}`,
          "---",
        ].join("\n"),
      );
    
      const forecastText = `Forecast for ${latitude}, ${longitude}:\n\n${formattedForecast.join("\n")}`;
    
      return {
        content: [
          {
            type: "text",
            text: forecastText,
          },
        ],
      };
    },
  • Input schema for the get_forecast tool using Zod validation for latitude and longitude parameters.
    {
      latitude: z.number().min(-90).max(90).describe("Latitude of the location"),
      longitude: z
        .number()
        .min(-180)
        .max(180)
        .describe("Longitude of the location"),
    },
  • src/index.ts:67-69 (registration)
    Registration of the 'get_forecast' tool on the MCP server, specifying name and description.
    server.tool(
      "get_forecast",
      "Get weather forecast for a location",
  • Helper utility function used in the get_forecast handler to perform API requests to the NWS with proper headers and error handling.
    export async function makeNWSRequest<T>(url: string): Promise<T | null> {
      const headers = {
        "User-Agent": USER_AGENT,
        Accept: "application/geo+json",
      };
    
      try {
        const response = await fetch(url, { headers });
        if (!response.ok) {
          throw new Error(`HTTP error! status: ${response.status}`);
        }
        return (await response.json()) as T;
      } catch (error) {
        console.error("Error making NWS request:", error);
        return null;
      }
    }
  • TypeScript interfaces defining the structure of NWS API responses used in the get_forecast tool (ForecastResponse, PointsResponse, ForecastPeriod).
    export interface ForecastPeriod {
      name?: string;
      temperature?: number;
      temperatureUnit?: string;
      windSpeed?: string;
      windDirection?: string;
      shortForecast?: string;
    }
    
    export interface AlertsResponse {
      features: AlertFeature[];
    }
    
    export interface PointsResponse {
      properties: {
        forecast?: string;
      };
    }
    
    export interface ForecastResponse {
      properties: {
        periods: ForecastPeriod[];
      };
    }

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.1/5.0
Behavior2/5

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

With no annotations provided, the description must disclose behavioral traits, but it only states 'Get weather forecast for a location'. It does not mention what kind of forecast (current, daily, hourly), potential destructive actions (none implied but not confirmed), or any required permissions. The agent has no insight into side effects or return behavior.

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 a single, front-loaded sentence with no wasted words. It is appropriately concise for a simple tool with two well-documented parameters.

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 tool's low complexity (2 params, no output schema, no annotations), the description is minimally adequate. However, it omits key details such as the forecast type, time horizon, units, and any specifics about the response. A slightly more complete description would improve usability.

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 100% with each parameter having a clear description. The tool description adds no further parameter meaning. Baseline score of 3 is appropriate since the schema already documents parameters adequately.

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 action (get) and resource (weather forecast) with a location qualifier. However, it does not differentiate from the sibling tool 'get_alerts', which likely also relates to weather. Without distinguishing context, the agent may not know when to choose one over the other.

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 alternative 'get_alerts'. There is no mention of prerequisites, typical use cases, or selection criteria, leaving the agent without context to make an informed choice.

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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