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MCP FishBase Server

by lundgrenalex

get_morphology

Retrieve morphological and physiological data for marine species from FishBase to analyze physical characteristics and biological traits.

Instructions

Get morphological and physiological data for a species

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
species_nameYesScientific name of the species

Implementation Reference

  • src/index.ts:96-109 (registration)
    Registration of the 'get_morphology' MCP tool in the server's listTools response, including its input schema definition.
    {
      name: "get_morphology",
      description: "Get morphological and physiological data for a species",
      inputSchema: {
        type: "object",
        properties: {
          species_name: {
            type: "string",
            description: "Scientific name of the species",
          },
        },
        required: ["species_name"],
      },
    },
  • Handler for the 'get_morphology' tool in the MCP server's CallToolRequestSchema, which calls FishBaseAPI.getMorphology and returns the result as formatted JSON text content.
    case "get_morphology":
      return {
        content: [
          {
            type: "text",
            text: JSON.stringify(
              await fishbaseAPI.getMorphology(args.species_name as string),
              null,
              2
            ),
          },
        ],
      };
  • Core implementation of getMorphology method in FishBaseAPI class. Retrieves the species SpecCode and filters the 'morphdat' table data for morphological information.
    async getMorphology(speciesName: string): Promise<any[]> {
      try {
        const speciesData = await this.getSpecies(speciesName);
        if (speciesData.length === 0) {
          throw new Error(`Species not found: ${speciesName}`);
        }
        
        const specCode = speciesData[0].SpecCode;
        const morphData = await this.queryTable('morphdat');
        
        return morphData.filter((row: any) => row.SpecCode === specCode);
      } catch (error) {
        throw new Error(`Failed to get morphology data: ${error}`);
      }
    }
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 states the tool retrieves data but does not specify whether it's a read-only operation, if it requires authentication, potential rate limits, or what the output format might be (e.g., structured data, text). This leaves key behavioral traits unclear for a tool with no output schema.

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 directly states the tool's purpose without unnecessary words. It is front-loaded and efficiently conveys the core functionality, making it easy to parse and understand 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 the lack of annotations and output schema, the description is incomplete for a data retrieval tool. It does not explain what type of data is returned (e.g., JSON structure, text summary), potential errors, or how it differs from sibling tools, leaving gaps that could hinder an agent's ability to use it effectively.

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 the single parameter 'species_name' fully documented in the schema as 'Scientific name of the species'. The description adds no additional meaning or context beyond this, such as examples or constraints, so it meets the baseline for high schema coverage without compensating further.

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 action ('Get') and the resource ('morphological and physiological data for a species'), making the purpose understandable. However, it does not explicitly differentiate this tool from sibling tools like 'get_species' or 'get_ecology', which might also retrieve species-related data, leaving some ambiguity about its specific scope.

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, such as 'get_species' or 'get_ecology', nor does it mention any prerequisites or exclusions. Without such context, an agent must infer usage based on the tool name alone, which is insufficient for optimal 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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