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gnomad-genetics-mcp-server

by io.github.cyanheads

gnomad-genetics-mcp-server: search clinvar

gnomad_search_clinvar
Read-onlyIdempotent

Search ClinVar (NCBI E-utilities) for a gene and return its classified variants — clinical significance, review status with a 0–4 star rating, associated conditions, molecular consequences, and submission counts — turning the variant-level significance gnomAD joins into a gene-panel curation view. Optionally filter by clinical_significance (e.g. pathogenic) and a minimum star rating. The full set is staged on a DataCanvas table named clinvar_variants with an inline preview; query it with gnomad_dataframe_query to rank or count across the complete set. Keyless, but honors NCBI_API_KEY for a higher rate limit. When the canvas is disabled the tool returns a capped inline preview with spilled=false. Credit: ClinVar, NCBI.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
geneYesGene HGNC symbol (e.g. PCSK9). ClinVar indexes HGNC symbols only — Ensembl gene IDs (ENSG…) are not resolved here, unlike the other gnomAD tools; resolve one to its symbol via ensembl_lookup_gene.
canvas_idNoOptional canvas ID from a prior call, to reuse the same canvas. Reusing it REPLACES (overwrites) the clinvar_variants table with this call's results — it does not append. Omit to start a fresh canvas; the response returns a new one.
min_review_starsNoKeep only variants with at least this gold-star review rating (0–4).
clinical_significanceNoFilter by ClinVar clinical significance term (e.g. pathogenic, likely_pathogenic, benign).

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
errorNoPresent when the call failed. Absent on success.
totalNoTotal matching ClinVar records (staged row count when spilled, else preview length).
noticeNoGuidance when no ClinVar records matched, or when the canvas is disabled and the preview is capped.
previewNoInline preview rows — the immediate answer.
spilledNoTrue when the full result was staged on the canvas beyond the preview.
canvas_idNoCanvas ID — pass to gnomad_dataframe_query. Empty string when canvas is disabled.
table_nameNoCanvas table holding the full set (clinvar_variants); empty when not spilled.

TDQS

A3.5/5.0
Behavior1/5

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

Annotation Contradiction: readOnlyHint is true, but the description says the full set is staged on a DataCanvas table and the schema notes that reusing a canvas_id REPLACES the table. This describes a write/side-effect behavior that conflicts with the read-only annotation.

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 front-loaded with the purpose, then covers filters, DataCanvas staging, query alternative, API-key behavior, and fallback behavior. It is somewhat dense and includes minor extras like 'Credit: ClinVar, NCBI', but every major sentence adds value.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description covers the external source, rate-limit behavior, DataCanvas staging, disabled-canvas fallback, filtering options, and the recommended way to query the complete result set. The output schema handles return-value expectations. The readOnlyHint contradiction leaves the overall behavioral context slightly incoherent, preventing a perfect score.

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 four parameters thoroughly. The description adds only light extra meaning, such as examples for clinical_significance ('pathogenic') and the 0–4 star rating concept; it does not materially compensate 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 action and resource: 'Search ClinVar (NCBI E-utilities) for a gene and return its classified variants.' It clearly differentiates this tool from gnomAD-native siblings by emphasizing an external ClinVar source, gene-level classification, and a 'gene-panel curation view.'

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 supplies clear context: you use this tool when you need ClinVar variant classifications for a gene, with optional filters and a staged DataCanvas table for further querying via gnomad_dataframe_query. It does not explicitly state when not to use it or name alternative tools beyond the dataframe query direction.

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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TDQS

A4.2/5.0
Disambiguation5/5

Every tool has a clearly distinct role: specific variant lookup, gene constraint, coverage, ClinVar search, and canvas SQL describe/query. The closest pair, gnomad_get_variant and gnomad_list_gene_variants, is separated by input type and the depth of data returned.

Naming Consistency4/5

Most tools follow a gnomad_<verb>_<object> pattern like get_coverage, get_variant, list_gene_variants, and search_clinvar. The two canvas helpers break this with gnomad_dataframe_describe and gnomad_dataframe_query, but they form a readable and internally consistent sub-pattern.

Tool Count5/5

Seven tools is well-scoped for a gnomAD/ClinVar genetics server. Each tool addresses a distinct query need, and the two dataframe utilities add real analytic value without bloating the API.

Completeness5/5

The surface covers the core read-only workflows: variant lookup, gene variant listing with filters, constraint, coverage, and ClinVar curation. The dataframe query path prevents dead ends when working with large staged result sets.

Resources