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plant-genomics-mcp

by musharna

VEP: Variant Effect

vep_annotate
Read-onlyIdempotent

Predict molecular consequences of a variant using Ensembl VEP. Supply a genomic region and alternate allele to receive consequence terms, IMPACT, and SIFT/PolyPhen scores.

Instructions

Predict a variant's molecular consequences with Ensembl VEP (rest.ensembl.org; free, no key). Variant-first (not locus-first): supply an Ensembl region (chr:start-end:strand, e.g. '1:10000-10000:1') and an alternate allele (e.g. 'C'); returns the most-severe consequence plus one row per overlapping transcript (consequence terms, IMPACT, and SIFT/PolyPhen when the variant is coding-missense). found=false when Ensembl reports no overlapping feature. Works for all 12 organisms. Defaults to arabidopsis_thaliana; pass organism= for other species.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
alleleYesAlternate allele, e.g. 'C' (or 'A/C', an insertion, etc.)
regionYesEnsembl region chr:start-end:strand, e.g. '1:10000-10000:1'
organismNoPlant organism — accepts canonical slug (arabidopsis_thaliana), scientific or common name, or NCBI taxidarabidopsis_thaliana

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
endNo
foundYesTrue if VEP returned an overlapping feature
inputNoVEP echo of the parsed input
startNo
alleleYesAlternate allele, e.g. 'C'
regionYesEnsembl region, e.g. '1:10000-10000:1'
organismYesResolved Ensembl species slug
allele_stringNo
assembly_nameNoAssembly the call is against
seq_region_nameNo
most_severe_consequenceNoMost severe SO term
transcript_consequencesNoPer-transcript {gene_id, transcript_id, consequence_terms, impact, sift_*, …}
Behavior5/5

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

Annotations already declare safe, idempotent, read-only. The description adds significant behavioral context: free API, no key needed, returns most-severe consequence per transcript, found=false when no features, works for 12 organisms, default organism, and output format. Adds value beyond annotations with no contradictions.

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 well-structured with front-loaded core purpose, followed by details on input, output, and scope. While it is on the longer side, all sentences provide useful information and are necessary given the tool's complexity.

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 tool has 3 parameters (100% schema coverage), an output schema, and clear annotations. The description covers remaining aspects: free API, organism support, found flag, and consequence detail. Everything an agent needs is present.

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 baseline is 3. The description enriches parameters with format examples for region (chr:start-end:strand), allele example ('C'), and organism accepted types (slug, name, taxid) and default. This provides valuable guidance beyond 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 uses specific verb 'predict' and resource 'molecular consequences with Ensembl VEP'. It explicitly states the tool is variant-first (not locus-first), and distinguishes from sibling tools that handle loci or other analyses, making the purpose clear.

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 explains when to use (variant effect prediction), specifies variant-first approach, and provides examples of input format. It does not explicitly exclude alternative tools but implies context through sibling list; clear usage context is 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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