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io.github.rcsb/rcsb-mcp

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by rcsb

rcsb_find_organisms

Read-onlyIdempotent

Resolve common names or clades like 'human' or 'bacteria' to NCBI taxonomy IDs, enabling precise taxonomy-based PDB structure searches instead of keyword guessing.

Instructions

Resolve a free-text organism, common name, or clade (e.g. human, mouse, baker's yeast, Escherichia coli, mammals, bacteria, primates) to NCBI Taxonomy ids, for precise taxonomy-based PDB searches instead of keyword guessing.

Use when a request restricts structures by SOURCE ORGANISM or any higher taxon — a common name you want as a canonical taxon ("human", "fruit fly"), or a CLADE, which a plain name search cannot expand. Resolve the phrase to a taxon id here, then search by it — see the resolver guidance in the server instructions for the attribute path, lineage semantics and the id-typing gotcha.

Args: query: Free-text organism / clade / common name, e.g. "human", "mammals", "E. coli". limit: Max taxa to return. with_pdb_counts: If true (default), annotate each taxon with pdb_entry_count (PDB entries from it or any organism beneath it, via taxonomy_lineage.id) — this also disambiguates a species from its strains.

Returns: {query, count, taxa:[{tax_id, scientific_name, common_name, rank, pdb_entry_count?}]}.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
queryYes
with_pdb_countsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false. The description adds meaningful behavioral context beyond these: pdb_entry_count includes descendants via taxonomy_lineage.id, and with_pdb_counts 'disambiguates a species from its strains'. It also hints at an 'id-typing gotcha'. While it does not mention rate limits or auth, for a read-only resolver this is sufficient context.

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 well-structured: purpose, usage, args, returns. It is front-loaded with the core action and examples. Every sentence contributes value, including the resolver guidance pointer. No redundant fluff; the length is appropriate for a tool with nuanced behavior.

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?

The description includes a Returns section that matches the output schema, explains the resolver workflow, and covers the three parameters. Given the tool's moderate complexity and the presence of annotations, this description is complete. It even tells the user where to find additional resolver guidance, making it self-contained.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, but the description fully compensates. Each parameter is explained with examples: query as free-text organism/clade, limit as max taxa, and with_pdb_counts with detailed semantics (annotating pdb_entry_count and disambiguation). This adds far more meaning than the bare schema types and defaults.

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 opens with a specific verb and resource: 'Resolve a free-text organism, common name, or clade ... to NCBI Taxonomy ids'. It clearly distinguishes this from sibling search tools by emphasizing 'for precise taxonomy-based PDB searches instead of keyword guessing' and provides concrete examples. Purpose is unmistakable and well-scoped.

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?

It explicitly states when to use: 'Use when a request restricts structures by SOURCE ORGANISM or any higher taxon' and contrasts with a 'plain name search' that cannot expand clades. It also provides a workflow: 'Resolve the phrase to a taxon id here, then search by it' and points to server instructions for attribute path and lineage semantics. This is strong, actionable usage guidance.

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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