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RyanCardin15

LocalTides MCP Server

get_station_details

Retrieve detailed station information, including ID, output format (JSON/XML), and units (English/Metric), for accurate water level and tide data analysis.

Instructions

Get detailed information about a station

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
formatNoOutput format (json, xml)
stationYesStation ID
unitsNoUnits to use ("english" or "metric")

Implementation Reference

  • Implements the core logic to fetch detailed station information from NOAA's metadata API by constructing the endpoint `/stations/{station}/details.{format}` and calling fetchMetadataApi.
    async getStationDetails(params: Record<string, any>): Promise<any> {
      const { station, ...rest } = params;
      const endpoint = `/stations/${station}/details.` + (rest.format || 'json');
      
      return this.fetchMetadataApi(endpoint, rest);
    }
  • Registers the get_station_details tool in the McpServer class using the MCPTool interface, with schema validation and delegation to NoaaService.
    const getStationDetails: MCPTool = {
      name: "get_station_details",
      description: "Get detailed information about a station",
      inputSchema: GetStationDetailsSchema,
      handler: async (params) => {
        return this.noaaService.getStationDetails(params);
      }
    };
  • Zod schema defining input parameters for get_station_details: required station ID, optional units (english/metric), optional format (json/xml).
    export const GetStationDetailsSchema = z.object({
      station: StationSchema,
      units: UnitsSchema,
      format: z.enum(['json', 'xml']).optional().describe('Output format (json, xml)'),
    });
  • Alternative registration of get_station_details tool using FastMCP's addTool method, with inline Zod parameters schema, error handling, and JSON stringification of result.
    server.addTool({
      name: 'get_station_details',
      description: 'Get detailed information about a station',
      parameters: z.object({
        station: StationSchema,
        format: z.enum(['json', 'xml']).optional().describe('Output format (json, xml)'),
        units: UnitsSchema,
      }),
      execute: async (params) => {
        try {
          const result = await noaaService.getStationDetails(params);
          return JSON.stringify(result);
        } catch (error) {
          if (error instanceof Error) {
            throw new Error(`Failed to get station details: ${error.message}`);
          }
          throw new Error('Failed to get station details');
        }
      }
    });
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It only states it 'gets' information, implying a read-only operation, but lacks details on permissions, rate limits, error handling, or response format. For a tool with no annotation coverage, this is insufficient to inform agent 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, efficient sentence with no wasted words, making it easy to parse. It's front-loaded with the core action and resource, though it could benefit from more detail given the lack of other guidance.

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 implied by sibling tools (e.g., various station-related data types) and no output schema, the description is incomplete. It doesn't specify what 'detailed information' includes (e.g., metadata, measurements, trends), leaving gaps for an agent to understand the tool's full context and output.

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 description adds no meaning beyond the input schema, which has 100% coverage with clear descriptions for all parameters (station ID, output format, units). Since the schema fully documents parameters, the baseline score of 3 is appropriate, as the description doesn't compensate but also doesn't detract.

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 ('detailed information about a station'), making the purpose understandable. However, it doesn't differentiate this tool from sibling tools like 'get_stations' (which likely lists stations) or 'get_current_predictions' (which might provide predictions for stations), leaving room for ambiguity about what specific details are retrieved.

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 many sibling tools related to stations (e.g., 'get_stations', 'get_current_predictions'), it fails to specify if this is for metadata, real-time data, or other details, offering no context for 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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