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uniprot-mcp-server: get taxonomy

uniprot_get_taxonomy
Read-onlyIdempotent

Resolve a taxonomy record by NCBI taxon ID (e.g. 9606) or scientific name (e.g. "Homo sapiens") — provide exactly one. Returns the scientific and common name, mnemonic, rank, parent, and the full lineage. Set include_children to also fetch immediate child taxa (a separate lookup — not inline on the record). Use this to turn an organism name into the taxon ID that uniprot_search_proteins (organism_id) and uniprot_get_proteome (taxon_id) expect.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameNoOrganism scientific name, e.g. "Homo sapiens". Provide this OR taxon_id, not both. Matched against the scientific name.
taxon_idNoNCBI taxonomy ID, e.g. 9606. Provide this OR name, not both.
include_childrenNoWhen true, also fetch the immediate child taxa via a follow-up search. Defaults to false.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
errorNoPresent when the call failed. Absent on success.
taxonNoThe taxonomy record.
lineageNoFull lineage from root to the taxon's near ancestor.
childrenNoImmediate children. Present only when include_children is true.
childCountNoNumber of immediate children returned (when include_children is true).

TDQS

A4.7/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and openWorldHint=true, so the safety profile is covered. The description adds useful behavioral context: it notes that include_children triggers a separate follow-up lookup (not inline), and that the tool returns a specific set of fields. This goes beyond the annotations without contradicting them.

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 two sentences, front-loaded with the primary purpose, and every clause earns its place. It packs essential information (input options, output fields, include_children behavior, and cross-references to sibling tools) without redundancy. No wasted words.

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?

Given the tool's moderate complexity (3 params, output schema present, annotations provided), the description is complete. It covers input constraints, output contents, the optional children behavior, and how it integrates with sibling tools. The output schema exists, so return values don't need elaboration. This is a well-rounded description for the context.

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?

Schema description coverage is 100%, so the schema already documents all three parameters well. The description adds value by clarifying the mutual exclusivity of name and taxon_id ('provide exactly one') and by explaining the purpose of include_children as a separate lookup. This is slightly above the baseline 3 because it reinforces the constraint and adds context about the follow-up behavior.

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 tool resolves a taxonomy record by NCBI taxon ID or scientific name, and lists the returned fields (scientific/common name, mnemonic, rank, parent, lineage). It distinguishes itself from siblings by explicitly mentioning how it feeds into uniprot_search_proteins and uniprot_get_proteome, which is a specific verb+resource+scope.

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

Usage Guidelines5/5

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

The description explicitly says to provide exactly one of name or taxon_id, and explains when to use this tool: to turn an organism name into a taxon ID for other tools. It also clarifies that include_children is a separate lookup, not inline, which prevents misuse. This is explicit when-to-use guidance with alternatives named.

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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TDQS

A4.7/5.0
Disambiguation5/5

Each tool has a clearly distinct purpose: retrieving entries, proteomes, sequences, taxonomy, mapping IDs, and searching proteins. There is no overlap; even the batch entry retrieval is distinct from the sequence-only retrieval.

Naming Consistency5/5

All tools follow a consistent verb_noun pattern with a consistent prefix: uniprot_get_entry, uniprot_get_proteome, uniprot_get_sequence, uniprot_get_taxonomy, uniprot_map_ids, uniprot_search_proteins. This makes it easy to predict available operations.

Tool Count5/5

With 6 tools, the server is well-scoped for its purpose of querying and retrieving UniProt data. Each tool serves a core function and no tool feels redundant.

Completeness4/5

The toolset covers the main workflows: search proteins, fetch full entries, fetch sequences, map IDs, resolve taxonomy, and fetch proteomes. Minor gaps include lack of tools for browsing taxonomy children inline or fetching isoforms in entries, but these can be worked around with existing tools.