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Ncbi Taxonomy

ncbi_taxonomy
Read-onlyIdempotent

Resolve organisms in the NCBI Taxonomy — the naming authority GenBank, ENA and DDBJ all classify against — from a tax id, scientific name or common name, returning the full ancestor lineage as tax ids, the immediate children, the taxonomic rank, every name the organism goes by, and live counts of how many assemblies, genes and protein-coding genes NCBI holds for it. AUTHORITATIVE for "what is the tax id for X" (the argument half the genomics APIs require) and for placing an organism in the tree. Accepts several at once; results are keyed by the query that produced them because upstream does not preserve request order.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
taxonsYesTax id, scientific name or common name — or several comma-separated: "9606", "Homo sapiens", "human", "9606,10090".

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive, openWorld). The description adds real behavioral value beyond them: the content of the return (lineage, children, rank, names, live assembly/gene counts) and the non-obvious quirk that results are keyed by query because upstream does not preserve request order, which directly affects how an agent must parse the response.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Purpose and return content are front-loaded in the first sentence, with authority and batching behavior following. It is dense and slightly run-on, but essentially every clause earns its place and nothing is redundant.

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

Completeness5/5

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

With no output schema, the description carries the burden of describing returns and does so fully (lineage, children, rank, names, live counts), while annotations cover safety. An agent has everything needed to call and interpret this tool 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 coverage is 100% and the single parameter's schema description already enumerates tax id, scientific name, common name and comma-separated forms with examples. The description's mention that it 'Accepts several at once' partly reinforces this, but adds no syntax or format detail beyond the schema, so the baseline 3 is appropriate.

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?

States a specific verb (Resolve) and resource (organisms in the NCBI Taxonomy) and lists exactly what comes back: ancestor lineage as tax ids, immediate children, rank, all names, and live counts. It also pins its niche against the broader genomics family by calling itself AUTHORITATIVE for 'what is the tax id for X', so an agent can distinguish it from ncbi_gene_by_symbol and ncbi_genome_reports.

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?

Explicitly states when to reach for it — the authoritative source for resolving a tax id and for placing an organism in the tree. It does not name a sibling as an alternative or describe when NOT to use it, but the intended use case is unambiguous.

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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