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ITIS MCP Server

by knustx

search_by_rank

Find organisms in the ITIS database by specifying taxonomic rank such as Species, Genus, or Family to retrieve relevant biological classifications.

Instructions

Search for organisms by their taxonomic rank in ITIS database.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
rankYesTaxonomic rank (e.g., "Species", "Genus", "Family", "Order", "Class", "Phylum", "Kingdom")
rowsNoNumber of results to return (default: 10)
startNoStarting index for pagination (default: 0)

Implementation Reference

  • Core implementation of search by taxonomic rank: calls base search method with filter rank:"${rank}"
    async searchByTaxonomicRank(rank: string, options: Partial<ITISSearchOptions> = {}): Promise<ITISResponse> {
      return this.search({
        ...options,
        filters: {
          ...options.filters,
          rank: `"${rank}"`
        }
      });
    }
  • MCP CallToolRequestSchema handler case for 'search_by_rank': extracts parameters, calls ITISClient method, returns formatted JSON response
    case 'search_by_rank': {
      const { rank, rows, start } = args as any;
      const result = await itisClient.searchByTaxonomicRank(rank, { rows, start });
      return {
        content: [
          {
            type: 'text',
            text: JSON.stringify({
              rank,
              totalResults: result.response.numFound,
              start: result.response.start,
              results: result.response.docs,
            }, null, 2),
          },
        ],
      };
    }
  • Input schema and metadata for the search_by_rank tool, included in the exported tools array
    {
      name: 'search_by_rank',
      description: 'Search for organisms by their taxonomic rank in ITIS database.',
      inputSchema: {
        type: 'object',
        properties: {
          rank: {
            type: 'string',
            description: 'Taxonomic rank (e.g., "Species", "Genus", "Family", "Order", "Class", "Phylum", "Kingdom")',
          },
          rows: {
            type: 'number',
            description: 'Number of results to return (default: 10)',
          },
          start: {
            type: 'number',
            description: 'Starting index for pagination (default: 0)',
          },
        },
        required: ['rank'],
      },
    },
  • src/index.ts:22-22 (registration)
    Call to setupToolHandlers which registers ListToolsRequest and CallToolRequest handlers, making search_by_rank available via the tools array and switch dispatcher
    setupToolHandlers(server, itisClient);
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 mentions searching in the 'ITIS database', which implies a read-only operation, but doesn't detail aspects like rate limits, authentication needs, error handling, or what the search results entail (e.g., format, fields). For a search tool with zero annotation coverage, this leaves significant gaps in understanding its 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: 'Search for organisms by their taxonomic rank in ITIS database.' It is front-loaded with the core purpose, has no unnecessary words, and earns its place by clearly stating the tool's function. This is an excellent example of conciseness.

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

Completeness3/5

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

Given the tool's moderate complexity (3 parameters, no output schema, no annotations), the description is minimally adequate. It states what the tool does but lacks details on behavioral traits, usage context, and result handling. Without an output schema, it doesn't explain return values, which could be a gap. However, it covers the basic purpose, making it just sufficient for a simple search operation.

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, with clear explanations for 'rank', 'rows', and 'start'. The description adds no additional parameter semantics beyond what the schema provides, such as examples of valid ranks or pagination behavior. Given the high schema coverage, a 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 tool's purpose: 'Search for organisms by their taxonomic rank in ITIS database.' It specifies the verb ('Search'), resource ('organisms'), and constraint ('by their taxonomic rank'), which is specific and actionable. However, it doesn't explicitly differentiate from sibling tools like 'search_by_kingdom' or 'search_by_scientific_name', which also search the ITIS database but by different criteria, so it falls short of a perfect score.

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. It doesn't mention sibling tools such as 'search_by_kingdom' or 'search_by_scientific_name', nor does it specify scenarios where taxonomic rank-based search is preferred over other search methods. Without this context, users might struggle to choose the right tool for their needs.

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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