Skip to main content
Glama
mattjegan

eBird MCP Server

by mattjegan

get_taxonomy

Retrieve eBird's complete bird species taxonomy with codes, names, and classifications. Filter by species, category, or version, and choose response format for integration.

Instructions

Get the eBird taxonomy (list of all species with codes, names, and classification).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
catNoTaxonomic category filter (e.g., 'species', 'issf', 'hybrid')
fmtNoResponse formatjson
localeNoLanguage for common namesen
speciesNoComma-separated species codes to fetch (e.g., 'cangoo,barswa')
versionNoSpecific taxonomy version

Implementation Reference

  • Handler function that constructs parameters from args and fetches taxonomy data via makeRequest from the eBird API endpoint.
    async (args) => {
      const params: Record<string, string | number | boolean> = {
        fmt: args.fmt,
        locale: args.locale,
      };
      if (args.cat) params.cat = args.cat;
      if (args.species) params.species = args.species;
      if (args.version) params.version = args.version;
    
      const result = await makeRequest("/ref/taxonomy/ebird", params);
      return { content: [{ type: "text", text: JSON.stringify(result, null, 2) }] };
    }
  • Zod schema defining input parameters for the get_taxonomy tool.
    {
      cat: z.string().optional().describe("Taxonomic category filter (e.g., 'species', 'issf', 'hybrid')"),
      fmt: z.enum(["json", "csv"]).default("json").describe("Response format"),
      locale: z.string().default("en").describe("Language for common names"),
      species: z.string().optional().describe("Comma-separated species codes to fetch (e.g., 'cangoo,barswa')"),
      version: z.string().optional().describe("Specific taxonomy version"),
    },
  • src/index.ts:456-478 (registration)
    Registration of the get_taxonomy tool using server.tool, including description, schema, and handler.
    server.tool(
      "get_taxonomy",
      "Get the eBird taxonomy (list of all species with codes, names, and classification).",
      {
        cat: z.string().optional().describe("Taxonomic category filter (e.g., 'species', 'issf', 'hybrid')"),
        fmt: z.enum(["json", "csv"]).default("json").describe("Response format"),
        locale: z.string().default("en").describe("Language for common names"),
        species: z.string().optional().describe("Comma-separated species codes to fetch (e.g., 'cangoo,barswa')"),
        version: z.string().optional().describe("Specific taxonomy version"),
      },
      async (args) => {
        const params: Record<string, string | number | boolean> = {
          fmt: args.fmt,
          locale: args.locale,
        };
        if (args.cat) params.cat = args.cat;
        if (args.species) params.species = args.species;
        if (args.version) params.version = args.version;
    
        const result = await makeRequest("/ref/taxonomy/ebird", params);
        return { content: [{ type: "text", text: JSON.stringify(result, null, 2) }] };
      }
    );
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. It states the tool retrieves taxonomy data but does not disclose behavioral traits such as rate limits, authentication needs, pagination, or error handling. For a read operation with no annotation coverage, this is a significant gap in transparency.

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 without unnecessary details. Every word earns its place, 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.

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 (5 optional parameters) and lack of annotations or output schema, the description is minimally adequate. It covers the purpose but misses behavioral context and usage guidelines, leaving gaps that could hinder effective tool selection and invocation by an agent.

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 all five parameters thoroughly. The description adds no additional meaning beyond implying a comprehensive list, which aligns with the schema but does not compensate for or enhance parameter understanding. Baseline 3 is appropriate when schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

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 ('eBird taxonomy'), specifying it returns a list of all species with codes, names, and classification. It distinguishes from sibling tools like 'get_species_list' or 'get_taxonomic_groups' by focusing on the comprehensive taxonomy rather than specific subsets or related data.

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 like 'get_species_list' or 'get_taxonomic_groups'. It lacks explicit context, prerequisites, or exclusions, leaving the agent to infer usage based on the purpose alone.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/mattjegan/ebird-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server