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RyanCardin15

noaa-tidesandcurrents-mcp

get_meteorological_data

Retrieve meteorological data from NOAA Tides and Currents API by specifying station, product (e.g., air_temperature, wind), date range, units, time zone, and output format (JSON, XML, CSV).

Instructions

Get meteorological data

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
begin_dateNoStart date (YYYYMMDD or MM/DD/YYYY)
dateNoDate to retrieve data for ("today", "latest", "recent", or specific date)
end_dateNoEnd date (YYYYMMDD or MM/DD/YYYY)
formatNoOutput format (json, xml, csv)
productYesProduct (air_temperature, wind, etc.)
rangeNoNumber of hours to retrieve data for
stationYesStation ID
time_zoneNoTime zone (gmt, lst, lst_ldt)
unitsNoUnits to use ("english" or "metric")

Implementation Reference

  • Core handler function that fetches meteorological data from NOAA API by calling fetchDataApi with the provided parameters including the product type.
    async getMeteorologicalData(params: Record<string, any>): Promise<any> {
      const { product, ...rest } = params;
      return this.fetchDataApi({
        ...rest,
        product
      });
    }
  • Zod schema defining input parameters for the get_meteorological_data tool, including station, product, date parameters, with validation refinement.
    export const GetMeteorologicalDataSchema = z.object({
      station: StationSchema,
      product: z.string().min(1).describe('Product (air_temperature, wind, etc.)'),
      date: DateSchema,
      begin_date: BeginDateSchema,
      end_date: EndDateSchema,
      range: RangeSchema,
      units: UnitsSchema,
      time_zone: TimeZoneSchema,
      format: FormatSchema,
    }).refine(
      data => (data.date || (data.begin_date && data.end_date) || (data.begin_date && data.range) || (data.end_date && data.range) || data.range),
      { message: "You must provide either 'date', 'begin_date' and 'end_date', 'begin_date' and 'range', 'end_date' and 'range', or just 'range'" }
    );
  • Tool registration in McpServer class: defines the MCPTool object with name, description, schema, and handler delegating to NoaaService.
    const getMeteorologicalData: MCPTool = {
      name: "get_meteorological_data",
      description: "Get meteorological data",
      inputSchema: GetMeteorologicalDataSchema,
      handler: async (params) => {
        return this.noaaService.getMeteorologicalData(params);
      }
    };
  • Alternative tool registration using FastMCP server.addTool, with inline Zod parameters schema and execute handler calling NoaaService.
    server.addTool({
      name: 'get_meteorological_data',
      description: 'Get meteorological data',
      parameters: z.object({
        station: StationSchema,
        product: z.string().min(1).describe('Product (air_temperature, wind, etc.)'),
        date: DateSchema,
        begin_date: BeginDateSchema,
        end_date: EndDateSchema,
        range: RangeSchema,
        units: UnitsSchema,
        time_zone: TimeZoneSchema,
        format: FormatSchema,
      }).refine(refineDateParams, { message: dateRefinementMessage }),
      execute: async (params) => {
        try {
          const result = await noaaService.getMeteorologicalData(params);
          return JSON.stringify(result);
        } catch (error) {
          if (error instanceof Error) {
            throw new Error(`Failed to get meteorological data: ${error.message}`);
          }
          throw new Error('Failed to get meteorological data');
        }
      }
    });
Behavior1/5

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

No annotations are provided, so the description carries full burden for behavioral disclosure. 'Get meteorological data' reveals nothing about authentication requirements, rate limits, data freshness/latency, error conditions, pagination, or what the response structure looks like. For a tool with 9 parameters and no output schema, this leaves the agent completely in the dark about how the tool actually behaves.

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 maximally concise at just three words. While this represents severe under-specification rather than ideal conciseness, from a pure structural perspective, there's zero wasted language. Every word ('Get', 'meteorological', 'data') contributes to the minimal meaning provided.

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

Completeness1/5

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

For a complex tool with 9 parameters, 2 required parameters, no annotations, and no output schema, the description is completely inadequate. The agent needs to understand what meteorological data means in this specific API context, how it differs from sibling tools, what the response contains, and any behavioral constraints. The three-word description provides none of this essential context.

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 has 100% description coverage with detailed parameter documentation, so the baseline is 3. The description adds no additional parameter information beyond what's already in the schema. It doesn't explain relationships between parameters (like how 'date' interacts with 'begin_date' and 'end_date'), provide examples, or clarify ambiguous aspects like what 'recent' means for the date parameter.

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

Purpose2/5

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

The description 'Get meteorological data' is a tautology that essentially restates the tool name. While it includes a verb ('Get') and resource ('meteorological data'), it lacks specificity about what meteorological data means in this context and doesn't distinguish this tool from its many siblings (like get_current_predictions, get_water_levels, etc.). It doesn't clarify if this is for historical data, forecasts, or current conditions.

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

Usage Guidelines1/5

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

The description provides absolutely no guidance on when to use this tool versus alternatives. With 22 sibling tools available (many related to water levels, tides, sun/moon events, and station data), the agent has no indication whether this tool is for weather data specifically, what timeframes it covers, or how it differs from other meteorological-related tools that might exist in the sibling list.

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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