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Glama
genebe-net

GeneBe MCP

Official
by genebe-net

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault

No arguments

Instructions

Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.

This server publishes no instructions, or was last inspected before Glama recorded them.

Capabilities

Features and capabilities supported by this server

Protocol revision2025-11-25

CapabilityDetails
tools
{
  "listChanged": false
}
prompts
{
  "listChanged": false
}
resources
{
  "subscribe": false,
  "listChanged": false
}

Tools

Functions exposed to the LLM to take actions

NameDescription
annotate_variantA

Annotate and classify one human genetic variant using GeneBe.

Start here for any question about a variant (what is it, is it pathogenic/benign, how common is it). Returns the ACMG verdict with points and criteria, population frequency (gnomAD), predictor scores (REVEL, AlphaMissense, SpliceAI, ...), ClinVar status, transcript consequences, and links to the GeneBe page to cite. Research use only; not a diagnosis.

explain_acmg_decision_pathA

Explain step by step why each classification criterion did or did not apply to a variant.

Use after annotate_variant when the user asks "why was this classified that way?". Returns an ASCII rendering of the decision tree with the evaluated conditions. By default it explains the germline ACMG verdict that annotate_variant returns; the somatic trees 'oncogenicity' (2022) and 'acgs-uk-onco' (2025) can be requested explicitly. Research use only.

convert_variantA

Convert a variant written in any notation into normalized hg38 genomic coordinates.

Use when you only need the chr/pos/ref/alt of a variant (for example to translate HGVS or an rsID), without annotation. Does not classify the variant; use annotate_variant for that.

get_variant_effectsA

List a variant's predicted molecular consequences on every overlapping transcript.

Returns per-transcript HGVS (c. and p.), consequence terms (e.g. missense_variant) and impact, most severe and MANE Select transcripts first. Lightweight: no frequencies or classification.

get_geneA

Look up a human gene: identifiers, location, MANE Select transcript, ClinGen gene-disease validity.

Use for questions about a gene rather than a specific variant. Transcripts are listed with MANE Select first and capped; check total_transcripts.

liftover_coordinateA

Convert a genomic position, interval or variant between genome builds (hg19, hg38, t2t).

Check status: RESOLVED means one result, AMBIGUOUS means several candidates, anything else means it could not be mapped (see errors). For variants, ref/alt are rebuilt against the target reference and warnings such as REF_MISMATCH may apply.

Prompts

Interactive templates invoked by user choice

NameDescription

No prompts

Resources

Contextual data attached and managed by the client

NameDescription

No resources

TDQS

A4.1/5.0

Scored across 6 tools

Disambiguation4/5

Each tool has a distinct primary purpose, and the descriptions explicitly steer agents between similar-sounding tools (e.g. annotate_variant vs get_variant_effects, convert_variant vs liftover_coordinate). Some boundary overlap remains between coordinate normalization/liftover and between annotation/effect retrieval, but it is manageable.

Naming Consistency5/5

All tool names use consistent snake_case with an action-object structure: get_gene, annotate_variant, convert_variant, get_variant_effects, liftover_coordinate, and explain_acmg_decision_path. The pattern is predictable even where the object is compound.

Tool Count5/5

Six tools are well scoped for a focused human genetics annotation server. Each tool covers a clear, non-redundant step in gene/variant lookup, interpretation, explanation, normalization, effect listing, and liftover.

Completeness4/5

The surface covers the core workflows: gene lookup, variant annotation/classification, ACMG explanation, variant normalization, transcript effects, and genome-build liftover. Minor gaps exist, such as batch annotation or direct phenotype/disease lookup, but no major workflow dead end is apparent.

Maintenance

ActivityMaintained
ResponsivenessNo issues