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plant-genomics-mcp

by musharna
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Python
Remote

1001 Genomes: Natural Variation

arabidopsis_natural_variation
Read-onlyIdempotent

Fetch 1001 Genomes SNP effects for an Arabidopsis locus, returning per-accession variant impacts, amino-acid changes, and gene span. Use it to explore natural variation across 1135 accessions.

Instructions

Fetch 1001 Genomes natural-variation SNP effects for an Arabidopsis locus (tools.1001genomes.org; free, no key) — the variation observed across 1135 resequenced natural accessions. Returns per-SNP effect rows (chromosome, position, accession id, effect, impact, amino-acid change, transcript) plus the gene's genomic span. variant_count is the true row total even when capped. ARABIDOPSIS-ONLY — any other organism raises OrganismNotSupported. Defaults to arabidopsis_thaliana.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
locusYesArabidopsis AGI locus, e.g. AT1G01060 (a bare AGI is transcript-scoped to .1)
cursorNonext_cursor from the previous page; omit for the first (#123)
organismNoArabidopsis only (the 1001 Genomes panel is A. thaliana)arabidopsis_thaliana

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
foundYesTrue once the effects endpoint returned 200
locusYes
totalYesHow many variant effects exist upstream for this query, all pages (pre-cap) (#123)
regionNoGenomic span, e.g. 'Chr1:33666..37840'
organismYesAlways arabidopsis_thaliana
returnedYesEffect rows returned (post-cap)
variantsNoPer-effect {chr, position, accession_id, effect, impact, amino_acid_change, …}
truncatedYesTrue if the effect list was capped
transcriptYesTranscript-scoped gene id used (e.g. AT1G01060.1)
next_cursorNoPass back as cursor= to get the rows after this page; null on the last page. Opaque, and bound to this tool and query (#123)
variant_countYesTotal effect rows (pre-cap)

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed4 schema fields changedv1.22.0
    • addedInput schema / properties / cursor
      Added value: +{
+  "description": "next_cursor from the previous page; omit for the first (#123)",
+  "type": "string"
+}
    • addedOutput schema / properties / next_cursor
      Added value: +{
+  "anyOf": [
+    {
+      "type": "string"
+    },
+    {
+      "type": "null"
+    }
+  ],
+  "default": null,
+  "description": "Pass back as cursor= to get the rows after this page; null on the last page. Opaque, and bound to this tool and query (#123)",
+  "title": "Next Cursor"
+}
    • addedOutput schema / properties / total
      Added value: +{
+  "description": "How many variant effects exist upstream for this query, all pages (pre-cap) (#123)",
+  "title": "Total",
+  "type": "integer"
+}
    • changedOutput schema / required
      Previous value: -[
-  "locus",
-  "organism",
-  "found",
-  "transcript",
-  "variant_count",
-  "returned",
-  "truncated"
-]New value: +[
+  "total",
+  "locus",
+  "organism",
+  "found",
+  "transcript",
+  "variant_count",
+  "returned",
+  "truncated"
+]
  2. Addedv1.18.2

TDQS

A4.4/5.0
Behavior5/5

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

Annotations already establish read-only, idempotent, and non-destructive behavior, and the description adds valuable context beyond that: the service is free and requires no key, pagination has a true-count caveat ('variant_count is the true row total even when capped'), and unsupported organisms raise a specific error. This helps an agent reason about external-service behavior, truncation, and failure modes.

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?

The description is three dense sentences with the core action front-loaded, followed by return content and critical caveats. Parentheticals add relevant detail without excessive padding. It could be slightly tighter, but every sentence carries useful information and the structure is logical.

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 output schema covers return values, so the description correctly focuses on selection criteria, organism restriction, pagination semantics, and external-service access details. An agent has enough information to decide whether to call this tool and to set expectations about errors and result limits. Nothing essential for correct invocation is missing.

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 documents all three parameters, including the AT1G01060 example, cursor usage, and organism default. The description repeats the default organism but does not add substantive parameter-level meaning beyond the schema. Baseline 3 is appropriate.

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 uses a specific verb and resource: 'Fetch 1001 Genomes natural-variation SNP effects for an Arabidopsis locus.' It clearly defines the data scope (1135 resequenced accessions) and the tool's specialized output, setting it apart from generic locus or variant tools. It also states the return payload concretely, so an agent knows exactly what this tool produces.

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 provides strong usage context by naming the data source, explaining the organism restriction ('ARABIDOPSIS-ONLY'), and stating the default organism. It also warns that non-Arabidopsis organisms raise OrganismNotSupported. However, it does not explicitly compare this tool to sibling alternatives like locus_variants, so the when-to-use-vs-alternatives guidance is implied rather than explicit.

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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