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plant-genomics-mcp

by musharna
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

Plant Ontology (PO/TO) Terms

locus_plant_ontology
Read-onlyIdempotent

Fetch Plant Ontology, Trait Ontology, and PECO condition annotations for a plant locus from Planteome, grouped by ontology and filtered by organism.

Instructions

Fetch Plant Ontology (PO) + Trait Ontology (TO) + experimental-condition (PECO) annotations for a plant locus from Planteome (browser.planteome.org, AmiGO2/GOlr; free, no API key). Complements locus_go_annotations: QuickGO serves GO (species-agnostic), Planteome serves the plant-specific ontologies — PO (anatomy + developmental stage), TO (traits). The locus is matched across Planteome's searchable bioentity fields and filtered by the organism's NCBI taxon. Returns annotations[] (term_id / term_name / ontology / aspect / evidence / reference) + a by_ontology rollup ({PO: [{term_id, term_name}, ...], TO: [...], PECO: [...]}) deduped on term_id. Planteome names genes by these locus ids for arabidopsis, rice, wheat and tomato only; other organisms are refused, and a gene Planteome has no record of is not found. Defaults to arabidopsis_thaliana; pass organism= for other species.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax annotations from Planteome (1–200, default 100)
locusYese.g. AT1G01010 (Arabidopsis), Os01g0100100 (rice)
organismNoPlant organism — accepts canonical slug (arabidopsis_thaliana), scientific or common name, or NCBI taxidarabidopsis_thaliana

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
locusYes
taxonYesNCBI taxon filter applied, e.g. NCBITaxon:3702
totalYesHow many annotations (Planteome numFound) exist upstream for this query, all pages (pre-cap) (#123)
organismYesCanonical organism slug
returnedYesRows in this payload (#123)
truncatedYesTrue when total > returned: more exist upstream than came back (#123)
annotationsYes
by_ontologyYesnamespace → [{term_id, term_name}, ...], deduped on term_id
numberOfHitsYesTotal annotations available upstream

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed4 schema fields changedv1.22.0
    • changedOutput schema / properties / returned / description
      Previous value: -"Number of annotations in annotations[]"New value: +"Rows in this payload (#123)"
    • addedOutput schema / properties / total
      Added value: +{
+  "description": "How many annotations (Planteome numFound) exist upstream for this query, all pages (pre-cap) (#123)",
+  "title": "Total",
+  "type": "integer"
+}
    • addedOutput schema / properties / truncated
      Added value: +{
+  "description": "True when total > returned: more exist upstream than came back (#123)",
+  "title": "Truncated",
+  "type": "boolean"
+}
    • changedOutput schema / required
      Previous value: -[
-  "locus",
-  "organism",
-  "taxon",
-  "numberOfHits",
-  "returned",
-  "annotations",
-  "by_ontology"
-]New value: +[
+  "total",
+  "truncated",
+  "locus",
+  "organism",
+  "taxon",
+  "numberOfHits",
+  "returned",
+  "annotations",
+  "by_ontology"
+]
  2. Addedv1.19.4

TDQS

A4.8/5.0
Behavior5/5

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

Annotations already cover the safety profile (readOnly, idempotent, openWorld, non-destructive), yet the description adds substantial context beyond them: no API key required, the four-organism support limit, refusal behavior, not-found semantics, dedup-on-term_id, and the exact return shape (annotations[] plus by_ontology rollup).

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?

Front-loads the core purpose and source before the sibling comparison and constraints, so nothing critical is buried. It is a single dense paragraph with several stacked clauses (return shape, dedup rule, organism limits) that could be split, but every sentence carries information.

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 read-only lookup with 3 params, full schema coverage, an output schema, and rich annotations, the description covers source, auth, scope limits, defaults, and failure modes. An agent has everything needed to call it correctly and interpret results.

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 coverage is 100%, so the baseline is 3, but the description adds real meaning to organism beyond the schema — the default (arabidopsis_thaliana) and the fact that slug, scientific/common name, or NCBI taxid are accepted, plus which organisms are actually eligible. Limit and locus already carry adequate schema descriptions.

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 (fetch) and resource (PO/TO/PECO annotations for a plant locus) with the source (Planteome, browser.planteome.org, AmiGO2/GOlr). It explicitly distinguishes itself from the closest sibling by naming locus_go_annotations and contrasting QuickGO's species-agnostic GO with Planteome's plant-specific ontologies.

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?

Explicitly routes the agent against an alternative (use locus_go_annotations for GO, this for plant-specific ontologies) and states hard conditions: only arabidopsis, rice, wheat, tomato are supported, other organisms are refused, and unknown genes are not found. Defaults and how to override organism are also given.

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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