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RyanCardin15

LocalTides MCP Server

get_tide_predictions

Retrieve tide prediction data for specific stations using station ID, date range, units, and output format. Access accurate water level information via the LocalTides MCP Server.

Instructions

Get tide prediction 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)
datumNoDatum to use (MLLW, MSL, etc.)
end_dateNoEnd date (YYYYMMDD or MM/DD/YYYY)
formatNoOutput format (json, xml, csv)
intervalNoInterval (hilo, hl, h, or a number for minutes)
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 tide predictions from NOAA API by setting product to 'predictions' and calling fetchDataApi.
    async getTidePredictions(params: Record<string, any>): Promise<any> {
      return this.fetchDataApi({
        ...params,
        product: 'predictions'
      });
    }
  • Registration of the 'get_tide_predictions' tool in McpServer, including name, description, input schema, and handler delegating to noaaService.
    const getTidePredictions: MCPTool = {
      name: "get_tide_predictions",
      description: "Get tide prediction data",
      inputSchema: GetTidePredictionsSchema,
      handler: async (params) => {
        return this.noaaService.getTidePredictions(params);
      }
    };
  • Zod input schema for validating parameters to the get_tide_predictions tool.
    export const GetTidePredictionsSchema = z.object({
      station: StationSchema,
      begin_date: BeginDateSchema,
      end_date: EndDateSchema,
      date: DateSchema,
      range: RangeSchema,
      datum: DatumSchema,
      units: UnitsSchema,
      time_zone: TimeZoneSchema,
      interval: IntervalSchema,
      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'" }
    );
  • Alternative registration of 'get_tide_predictions' tool using FastMCP server.addTool with inline schema and execute handler.
    server.addTool({
      name: 'get_tide_predictions',
      description: 'Get tide prediction data',
      parameters: z.object({
        station: StationSchema,
        begin_date: BeginDateSchema,
        end_date: EndDateSchema,
        date: DateSchema,
        range: RangeSchema,
        datum: DatumSchema,
        units: UnitsSchema,
        time_zone: TimeZoneSchema,
        interval: IntervalSchema,
        format: FormatSchema,
      }).refine(refineDateParams, { message: dateRefinementMessage }),
      execute: async (params) => {
        try {
          const result = await noaaService.getTidePredictions(params);
          return JSON.stringify(result);
        } catch (error) {
          if (error instanceof Error) {
            throw new Error(`Failed to get tide predictions: ${error.message}`);
          }
          throw new Error('Failed to get tide predictions');
        }
      }
    });
Behavior2/5

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

With no annotations provided, the description carries full burden for behavioral disclosure. 'Get tide prediction data' implies a read-only operation but doesn't specify authentication needs, rate limits, data freshness, or what happens with missing parameters. It lacks critical context for safe and effective use.

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 extremely concise at just three words with no wasted language. It's front-loaded with the essential action and resource. While it may be too brief for completeness, it achieves perfect conciseness within its limited scope.

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 10 parameters, no annotations, no output schema, and 21 sibling tools, the description is inadequate. It doesn't explain what 'tide prediction data' includes, how it differs from other water-related tools, or provide any behavioral context. The agent would struggle to use this effectively without additional information.

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 input schema has 100% description coverage, providing detailed documentation for all 10 parameters. The description adds no parameter-specific information beyond the tool name, so it doesn't enhance understanding beyond what the schema already provides. This meets the baseline for high schema coverage.

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

Purpose3/5

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

The description 'Get tide prediction data' states the basic action (get) and resource (tide prediction data), but it's vague about scope and doesn't differentiate from siblings like 'get_current_predictions' or 'get_water_levels'. It provides minimal but correct information about what the tool does.

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 about when to use this tool versus the many sibling tools (e.g., get_current_predictions, get_water_levels, get_extreme_water_levels). The description offers no context about appropriate use cases or exclusions, leaving the agent to infer usage from the tool name alone.

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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