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plant-genomics-mcp

by musharna
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Python
Remote

InterPro: Protein Domains

interpro_domains
Read-onlyIdempotent

Resolve a plant locus to its UniProt protein and retrieve InterPro domain and family annotations, including source databases, residue spans, and a count-by-type rollup for functional insight.

Instructions

Fetch the InterPro domain / family architecture for a locus (www.ebi.ac.uk/interpro; free, no key). Resolves the locus → UniProt accession, then returns the protein's InterPro entries — each with accession, name, type (domain / family / homologous_superfamily / …), source_database (Pfam appears here as source_database='pfam', not a separate tool), the integrated InterPro accession, and residue spans — plus a count_by_type rollup. A protein with no annotated domains returns found=true with an empty list; a locus with no UniProt entry raises a typed NotFoundError. domain_count is the true total even when the row list is page-capped. Works for all 12 organisms (UniProt-keyed). Defaults to arabidopsis_thaliana; pass organism= for other species.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
locusYese.g. AT4G09760 (Arabidopsis), Os01g0100100 (rice RAP-DB)
organismNoPlant organism — accepts canonical slug (arabidopsis_thaliana), scientific or common name, or NCBI taxidarabidopsis_thaliana

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
foundYesTrue once the locus resolved to a UniProt entry
locusYes
totalYesHow many InterPro entries on this protein exist upstream for this query, all pages (pre-cap) (#123)
domainsYes
returnedYesRows in this payload (#123)
accessionYesResolved UniProt accession
truncatedYesTrue if the row list was page-capped (< domain_count)
domain_countYesTotal InterPro entries (pre-cap)
count_by_typeYesRollup of entry count by type
upstream_versionNoInterPro release that produced THIS response, as stated by the upstream's own header (e.g. '109.0'). null means InterPro did not state one — never that no release exists, and never inferred from a separate metadata call, which can describe a different release than the one that answered.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed3 schema fields changedv1.22.0
    • addedOutput schema / properties / returned
      Added value: +{
+  "description": "Rows in this payload (#123)",
+  "title": "Returned",
+  "type": "integer"
+}
    • addedOutput schema / properties / total
      Added value: +{
+  "description": "How many InterPro entries on this protein exist upstream for this query, all pages (pre-cap) (#123)",
+  "title": "Total",
+  "type": "integer"
+}
    • changedOutput schema / required
      Previous value: -[
-  "locus",
-  "accession",
-  "found",
-  "domain_count",
-  "truncated",
-  "domains",
-  "count_by_type"
-]New value: +[
+  "total",
+  "returned",
+  "locus",
+  "accession",
+  "found",
+  "domain_count",
+  "truncated",
+  "domains",
+  "count_by_type"
+]
  2. Changed1 schema field changedv1.20.0
    • addedOutput schema / properties / upstream_version
      Added value: +{
+  "anyOf": [
+    {
+      "type": "string"
+    },
+    {
+      "type": "null"
+    }
+  ],
+  "default": null,
+  "description": "InterPro release that produced THIS response, as stated by the upstream's own header (e.g. '109.0'). null means InterPro did not state one — never that no release exists, and never inferred from a separate metadata call, which can describe a different release than the one that answered.",
+  "title": "Upstream Version"
+}
  3. Addedv1.18.2

TDQS

A4.5/5.0
Behavior5/5

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

Many behaviors are disclosed beyond the annotations: the locus-to-UniProt resolution workflow, the empty-list behavior for proteins without domains, the NotFoundError for loci without UniProt entries, page-capped row lists with domain_count as the true total, and the count_by_type rollup. This goes well beyond the read-only/idempotent 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 every sentence adds value: purpose, integration path, output shape, edge cases, pagination caveat, scope, and defaults. It is front-loaded with the core purpose, and no sentence is filler.

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?

For a tool with two well-documented parameters and an output schema, the description covers all necessary behavior: input resolution, return contents, edge cases, errors, pagination, organism scope, and default organism. Nothing an agent needs to call it correctly is left ambiguous.

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 100%, so the schema already fully documents locus and organism. The description adds minor context by noting the default organism and that organism accepts other species, but it does not add substantial syntax or format guidance beyond the 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 opens with a specific verb and resource: 'Fetch the InterPro domain / family architecture for a locus.' It clearly enumerates what is returned (accessions, names, types, source_database, spans, count_by_type) and distinguishes itself by noting Pfam appears via source_database='pfam', not as a separate tool.

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?

The description gives clear selection context: use this for InterPro domain/family data, it works for all 12 organisms, and Pfam data is included here. It mentions the default organism and the organism= parameter. It does not explicitly name excluded alternatives or state when not to use this tool, so it falls just short of a 5.

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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