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knustx

ITIS MCP Server

by knustx

get_statistics

Retrieve basic statistics about the ITIS database, including total record counts, to understand the scope of available taxonomic information.

Instructions

Get basic statistics about the ITIS database (total number of records).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • The primary MCP tool handler for 'get_statistics'. It invokes the ITIS client's getStatistics method and formats the response as JSON with total records count and current timestamp.
    case 'get_statistics': {
      const result = await itisClient.getStatistics();
      return {
        content: [
          {
            type: 'text',
            text: JSON.stringify({
              totalRecords: result.response.numFound,
              lastUpdated: new Date().toISOString(),
            }, null, 2),
          },
        ],
      };
    }
  • Tool schema definition for 'get_statistics', including name, description, and empty input schema (no parameters required).
    {
      name: 'get_statistics',
      description: 'Get basic statistics about the ITIS database (total number of records).',
      inputSchema: {
        type: 'object',
        properties: {},
      },
    },
  • Helper method in ITISClient class that performs a Solr count query ('*:*' with rows=0) to get total number of records in the ITIS database.
    async getStatistics(): Promise<ITISResponse> {
      return this.search({
        query: '*:*',
        rows: 0,
        fields: ['tsn']
      });
    }
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states this is a read operation ('Get'), implying it's non-destructive, but doesn't mention any behavioral traits like rate limits, authentication needs, response format, or whether it's real-time vs cached data. This is a significant gap for a tool with zero annotation coverage.

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 that directly states the tool's purpose without any fluff. It's front-loaded with the core action and resource, making it easy to parse. Every word earns its place.

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 has 0 parameters, no annotations, and no output schema, the description is minimally adequate. It explains what the tool does but lacks details on behavioral context, output format, or usage scenarios. For a simple read tool, this might suffice, but it leaves gaps in understanding how to interpret results.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has 0 parameters, and schema description coverage is 100%, so no parameter documentation is needed. The description appropriately doesn't discuss parameters, and the baseline for this scenario is 4, as it avoids unnecessary details while being complete for a parameterless tool.

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 resource ('basic statistics about the ITIS database'), specifying it returns 'total number of records'. However, it doesn't explicitly differentiate this from sibling tools like 'search_itis' or 'explore_taxonomy', which might also provide statistical insights.

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 on when to use this tool versus alternatives. The description mentions 'basic statistics' but doesn't clarify if this is for summary overviews, how it differs from search tools, or any prerequisites. This leaves the agent without context for tool 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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