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RyanCardin15

LocalTides MCP Server

get_high_tide_flooding_monthly

Retrieve monthly high tide flooding data for a specified station, customizable by date range, threshold level, and output format (JSON, XML, CSV) with LocalTides MCP Server.

Instructions

Get high tide flooding monthly count data for a station

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
begin_dateNoStart date (YYYYMMDD format)
datumNoDatum reference for DPAPI
end_dateNoEnd date (YYYYMMDD format)
formatNoOutput format (json, xml, csv)
stationYesStation ID
thresholdNoFlood threshold level
yearNoYear for analysis (YYYY format)

Implementation Reference

  • Handler function in DpapiService that fetches high tide flooding monthly count data from the NOAA DPAPI endpoint '/htf/monthly'.
    async getHighTideFloodingMonthly(params: Record<string, any>): Promise<any> {
      const { station, format = 'json', ...rest } = params;
      
      return this.fetchDpapi('/htf/monthly', {
        station,
        format,
        ...rest
      });
    }
  • Zod schema defining input parameters for the get_high_tide_flooding_monthly tool.
    export const HighTideFloodingMonthlySchema = z.object({
      station: StationSchema,
      format: FormatSchema,
      datum: DpapiDatumSchema,
      threshold: ThresholdSchema,
      begin_date: z.string().optional().describe('Start date (YYYYMMDD format)'),
      end_date: z.string().optional().describe('End date (YYYYMMDD format)'),
      year: YearSchema
    }).describe('Get high tide flooding monthly count data');
  • MCP tool registration for 'get_high_tide_flooding_monthly', including description, schema, and thin wrapper execute handler delegating to DpapiService.
    server.addTool({
      name: 'get_high_tide_flooding_monthly',
      description: 'Get high tide flooding monthly count data for a station',
      parameters: HighTideFloodingMonthlySchema,
      execute: async (params) => {
        try {
          const result = await dpapiService.getHighTideFloodingMonthly(params);
          return JSON.stringify(result);
        } catch (error) {
          if (error instanceof Error) {
            throw new Error(`Failed to get high tide flooding monthly data: ${error.message}`);
          }
          throw new Error('Failed to get high tide flooding monthly data');
        }
      }
    });
Behavior2/5

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. The description only states what the tool does, not how it behaves. It doesn't mention whether this is a read-only operation, what authentication might be required, rate limits, error conditions, or what the return format looks like (though format is a parameter). For a data retrieval tool with no annotation coverage, this is inadequate.

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 with zero wasted words. It's front-loaded with the core purpose and appropriately sized for what it communicates. Every word earns its place.

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 the complexity (7 parameters, no annotations, no output schema) and rich sibling context (multiple high tide flooding tools), the description is incomplete. It doesn't help the agent understand when to choose monthly data over daily/annual alternatives, doesn't explain behavioral aspects, and provides no output information. For a specialized data retrieval tool in a crowded namespace, this leaves significant gaps.

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%, so all parameters are documented in the schema. The description doesn't add any parameter-specific information beyond what's already in the schema. It mentions 'for a station' which aligns with the required 'station' parameter, but provides no additional context about parameter relationships or usage. Baseline 3 is appropriate when schema does the heavy lifting.

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: 'Get high tide flooding monthly count data for a station'. It specifies the verb ('Get'), resource ('high tide flooding monthly count data'), and scope ('for a station'). However, it doesn't explicitly differentiate from siblings like 'get_high_tide_flooding_annual' or 'get_high_tide_flooding_daily', which would require a 5.

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. With multiple sibling tools for high tide flooding data (annual, daily, monthly, seasonal, likelihoods, projections), the agent receives no help in selecting the appropriate tool for monthly data needs. No exclusions or prerequisites are mentioned.

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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