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mattjegan

eBird MCP Server

by mattjegan

get_species_list

Retrieve all bird species recorded in a specific region using eBird data, providing taxonomic codes for comprehensive regional biodiversity analysis.

Instructions

Get all species ever recorded in a region (species codes in taxonomic order).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
region_codeYesAny region code (country, subnational, location, etc.)

Implementation Reference

  • src/index.ts:355-365 (registration)
    Registration of the 'get_species_list' tool using McpServer.tool method, including name, description, input schema, and execution handler.
    server.tool(
      "get_species_list",
      "Get all species ever recorded in a region (species codes in taxonomic order).",
      {
        region_code: z.string().describe("Any region code (country, subnational, location, etc.)"),
      },
      async (args) => {
        const result = await makeRequest(`/product/spplist/${args.region_code}`);
        return { content: [{ type: "text", text: JSON.stringify(result, null, 2) }] };
      }
    );
  • Handler function that fetches the species list from eBird API endpoint `/product/spplist/{region_code}` using the shared makeRequest helper and returns formatted JSON response.
    async (args) => {
      const result = await makeRequest(`/product/spplist/${args.region_code}`);
      return { content: [{ type: "text", text: JSON.stringify(result, null, 2) }] };
    }
  • Zod schema defining the single input parameter 'region_code' as a string.
    {
      region_code: z.string().describe("Any region code (country, subnational, location, etc.)"),
    },
  • Shared utility function to make authenticated requests to the eBird API, used by all tools including get_species_list.
    async function makeRequest(endpoint: string, params: Record<string, string | number | boolean> = {}): Promise<unknown> {
      const url = new URL(`${BASE_URL}${endpoint}`);
      Object.entries(params).forEach(([key, value]) => {
        if (value !== undefined && value !== null) {
          url.searchParams.append(key, String(value));
        }
      });
    
      const response = await fetch(url.toString(), {
        headers: { "X-eBirdApiToken": API_KEY! },
      });
    
      if (!response.ok) {
        throw new Error(`eBird API error: ${response.status} ${response.statusText}`);
      }
    
      return response.json();
    }
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. It mentions the output format ('species codes in taxonomic order') but doesn't disclose behavioral traits like whether this is a read-only operation, potential rate limits, data freshness, or error conditions. For a tool with no annotation coverage, this leaves significant gaps in understanding how it behaves.

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 front-loads the core purpose and includes useful output details. Every word earns its place with no redundancy or wasted text, making it highly concise and well-structured.

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 no annotations and no output schema, the description provides basic purpose and output format but lacks completeness for a tool that returns species data. It doesn't cover behavioral aspects like data scope (e.g., historical vs. current), pagination, or error handling, which are important for an agent to use it correctly.

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 the schema already documents the 'region_code' parameter fully. The description adds no additional parameter semantics beyond what's in the schema (e.g., no examples of valid region codes or format details). Baseline 3 is appropriate when the 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 action ('Get all species ever recorded') and resource ('in a region'), with specificity about output format ('species codes in taxonomic order'). It distinguishes from siblings like 'get_species_observations' by focusing on comprehensive species lists rather than observations, though it doesn't explicitly name alternatives. This is clear but lacks explicit sibling differentiation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for retrieving comprehensive species lists in a region, but doesn't explicitly state when to use this tool versus alternatives like 'get_checklist' or 'get_species_observations'. It provides context (region-based species list) but no exclusions or named alternatives, leaving some ambiguity about 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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