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idss-mesa

neon-mcp

by idss-mesa

Search NEON taxonomy

neon_search_taxonomy
Read-onlyIdempotent

Search NEON's taxonomy lists by taxon type, rank, or exact scientific name with genus fallback to get Darwin Core taxonomic data for ecological research.

Instructions

NEON's taxonomy lists, paged: every taxon of a type (BIRD, PLANT, SMALL_MAMMAL, ...) or taxa by rank (kingdom ... genus) or exact scientific name with a genus fallback. Rows keep NEON's Darwin Core keys (dwc:scientificName, dwc:vernacularName, ...). No token. Next: follow page.nextOffset, or call neon_search_products for data about the taxa.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
genusNoGenus, e.g. Quercus.
limitNo
orderNo
class_NoClass (e.g. Aves).
familyNo
offsetNo
phylumNo
kingdomNo
verboseNoAll ranks and extra fields (nulls dropped); limit capped at 100.
divisionNo
scientific_nameNoExact scientific name (NEON matches exactly; a genus fallback runs when nothing matches).
taxon_type_codeNoALGAE, BEETLE, BIRD, FISH, HERPETOLOGY, MACROINVERTEBRATE, MOSQUITO, MOSQUITO_PATHOGENS, PLANT, SMALL_MAMMAL or TICK. Cannot be combined with a rank filter.
fuzzy_genus_fallbackNoRetry an unmatched 'Genus species' by genus and filter.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
pageYes
itemsYes
notesNo
sourceNo
filtersNo
resolvedNo
nextStepsNo
fuzzyFallbackUsedNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already indicate a safe read-only operation, and the description adds useful behavior beyond that: results are paged, no token is required, rows retain Darwin Core keys, and exact-name search falls back to genus. This is meaningful operational context that the agent would not otherwise know.

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?

Three sentences with no filler, front-loading the primary search modes and immediately adding the most important operational notes: no token, pagination, output keys, and the sibling fallback. Every sentence earns its place.

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

Completeness4/5

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

Despite 13 parameters, the description covers the main usage axes and points to the right sibling for product data. An output schema exists, so return values do not need elaboration. It stops just short of complete by not summarizing the taxon_type_code-versus-rank conflict or verbose-mode caveat, though those live in the schema.

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 only 46%, so the description partially compensates by explaining the broad modes (taxon type, rank, exact scientific name) and the genus fallback. However, several rank parameters like kingdom, phylum, division, order, and family are not elaborated in the description beyond the phrase 'taxa by rank', leaving the agent to rely on the sparse schema.

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 names a specific verb-resource pair ('search NEON taxonomy') and states the three search modes: taxon type, rank, and exact scientific name with genus fallback. It also distinguishes itself from the sibling neon_search_products by pointing there for data about the taxa.

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

Usage Guidelines4/5

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

It clearly scopes the tool to taxonomy lookups and gives practical routing guidance: paginate with page.nextOffset or switch to neon_search_products for taxon data. It does not explicitly say when not to use this tool, but the alternative is named and the context is clear.

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