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akaramanapp

Weather MCP Server

by akaramanapp

get-forecast

Retrieve weather forecasts for US locations by providing 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 inline async handler function for the 'get-forecast' tool. It takes latitude and longitude, fetches grid points and forecast data from the National Weather Service API, formats the forecast periods, and returns them as text content.
    async ({ latitude, longitude }) => {
      // Get grid point data
      const pointsData = await makeNWSRequest<PointsResponse>(
        `/points/${latitude.toFixed(4)},${longitude.toFixed(4)}`
      );
    
      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 - using full URL since the forecast URL is absolute
      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"),
      );
    
      return {
        content: [
          {
            type: "text",
            text: formattedForecast.join("\n"),
          },
        ],
      };
    },
  • Zod input schema for the 'get-forecast' tool, validating 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:143-224 (registration)
    Registration of the 'get-forecast' tool on the MCP server, specifying name, description, input schema, and handler.
    server.tool(
      "get-forecast",
      "Get weather forecast for a location",
      {
        latitude: z.number().min(-90).max(90).describe("Latitude of the location"),
        longitude: z.number().min(-180).max(180).describe("Longitude of the location"),
      },
      async ({ latitude, longitude }) => {
        // Get grid point data
        const pointsData = await makeNWSRequest<PointsResponse>(
          `/points/${latitude.toFixed(4)},${longitude.toFixed(4)}`
        );
    
        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 - using full URL since the forecast URL is absolute
        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"),
        );
    
        return {
          content: [
            {
              type: "text",
              text: formattedForecast.join("\n"),
            },
          ],
        };
      },
    );
  • Helper function used by the get-forecast handler to make API requests to the NWS weather service with axios and error handling.
    async function makeNWSRequest<T>(url: string): Promise<T | null> {
      try {
        const response = await api.get<T>(url);
        return response.data;
      } catch (error) {
        if (axios.isAxiosError(error)) {
          console.error("Error making NWS request:", error.message);
          if (error.response) {
            console.error("Response status:", error.response.status);
            console.error("Response data:", error.response.data);
          }
        } else {
          console.error("Unexpected error:", error);
        }
        return null;
      }
    }
  • TypeScript interfaces defining the structure of NWS API responses used in the get-forecast handler (PointsResponse and ForecastResponse). Also nearby ForecastPeriod (70-77).
    interface PointsResponse {
      properties: {
        forecast?: string;
      };
    }
    
    interface ForecastResponse {
      properties: {
        periods: ForecastPeriod[];
      };
    }
  • TypeScript interface for ForecastPeriod used in parsing forecast data.
    interface ForecastPeriod {
      name?: string;
      temperature?: number;
      temperatureUnit?: string;
      windSpeed?: string;
      windDirection?: string;
      shortForecast?: string;
    }

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

C2.9/5.0
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states what the tool does but doesn't describe any behavioral traits such as whether this is a read-only operation, if it requires authentication, rate limits, or what the response format might be. This is inadequate for a tool with zero annotation coverage.

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, clear sentence that efficiently conveys the core purpose without any unnecessary words. It's appropriately sized and front-loaded, making it easy for an agent to parse quickly.

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?

Given that there are no annotations and no output schema, the description is incomplete. It doesn't provide enough context about behavioral aspects, response format, or how this tool differs from its sibling. For a tool with this level of complexity and lack of structured data, the description should do more to compensate.

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?

The schema description coverage is 100%, with both parameters (latitude and longitude) well-documented in the schema. The description doesn't add any meaningful parameter semantics beyond what's already in the schema, so it meets the baseline score of 3.

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 verb ('Get') and resource ('weather forecast for a location'), making the purpose immediately understandable. However, it doesn't distinguish this tool from its sibling 'get-alerts', which likely provides different weather-related information, so it doesn't achieve the highest score.

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?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention the sibling 'get-alerts' or explain the difference between getting a forecast versus alerts, leaving the agent without context for tool selection.

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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