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io.github.rcsb/rcsb-mcp

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by rcsb

rcsb_seqcoord_alignments

Read-onlyIdempotent

Map sequence identifiers across PDB, UniProt, and NCBI to find corresponding proteins and aligned regions.

Instructions

Cross-reference a sequence across PDB, UniProt, and NCBI, with aligned ranges.

This is the tool for "which X identifiers correspond to this sequence?" across databases — including NCBI. The RCSB Data API only cross-references UniProt, so use THIS tool for NCBI RefSeq protein / genome mappings (and PDB<->UniProt too). The returned target_alignments[].target_id values are the mapped identifiers in the to_ref system, each with its aligned regions.

Examples: - "What NCBI proteins map to PDB entity 4HHB_1?" query_id="4HHB_1", from_ref="PDB_ENTITY", to_ref="NCBI_PROTEIN" - "Which PDB entities correspond to UniProt P69905?" query_id="P69905", from_ref="UNIPROT", to_ref="PDB_ENTITY"

Args: query_id: The sequence id, in the from_ref system's format — UNIPROT "P69905", NCBI_PROTEIN "NP_000508", NCBI_GENOME "NC_000016", PDB_ENTITY "4HHB_1" (entry_entityNumber), PDB_INSTANCE "4HHB.A" (entry.asym_id). PDB ids must be ENTITY-level, never a bare entry: for a whole entry, first get its polymer entity ids (4HHB -> 4HHB_1, 4HHB_2) and query each one. from_ref: Reference system of query_id. to_ref: Reference system to map onto. seq_range: Optional [begin, end] (1-based) to restrict the query region. fields: Optional GraphQL selection to override the default.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
fieldsNo
to_refYes
from_refYes
query_idYes
seq_rangeNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior5/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint. Description adds valuable context beyond annotations: explains output shape (target_alignments[].target_id), the ENTITY-level PDB ID requirement with examples, and the mapping semantics. No contradictions with annotations.

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 dense but well-structured: summary, usage context, examples, and parameter breakdown. Every sentence adds value; the length is justified by the tool's complexity. Front-loaded with a clear purpose statement.

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?

Complex cross-database tool with 5 parameters and an output schema. The description covers ID formats, constraints (entity-level requirement), optional parameters, and return value structure. No missing critical information for correct invocation.

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. It documents every parameter: query_id format per reference system, from_ref/to_ref enum behavior, seq_range as optional 1-based [begin, end], and fields as GraphQL selection override. It also provides example values for multiple systems.

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?

Description uses a specific verb ('Cross-reference') and resource ('sequence across PDB, UniProt, and NCBI'), clearly stating the tool's function and scope. It distinguishes itself from siblings by explicitly mentioning NCBI coverage, which is unique among the seqcoord tools.

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?

Provides explicit when-to-use guidance: 'This is the tool for "which X identifiers correspond to this sequence?" across databases — including NCBI.' It also contrasts with the RCSB Data API, telling agents to use this tool for NCBI mappings when the Data API only handles UniProt. Concrete examples further clarify use cases.

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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