io.github.cyanheads/gnomad-genetics-mcp-server

Fetch the full gnomAD population record for one or more variants — allele count/number/frequency overall and broken down per genetic-ancestry group, homozygote and hemizygote counts, quality flags, transcript consequence, in-silico predictor scores, and joined ClinVar clinical significance. The "how common, is it benign" answer in one call. Accepts a batch of up to ${MAX_VARIANT_BATCH} IDs (chrom-pos-ref-alt or rsID) with per-item partial success: a malformed or absent ID lands in failed[] without failing the others. An empty found[] for a well-formed ID means the variant is not in the chosen dataset — pair with gnomad_get_coverage to confirm the position is callable before concluding true absence.\nData source: gnomAD (Broad Institute) — https://gnomad.broadinstitute.org/

List every gnomAD variant in a gene, transcript, or region with allele frequencies and predicted consequences, optionally filtered to one consequence class (lof, missense, synonymous, other) and/or a maximum allele frequency. The full result is staged on a DataCanvas table named gene_variants and an inline preview is returned alongside canvas_id and table_name — run gnomad_dataframe_query against them to rank by AF, count by consequence, or group across the complete set rather than the preview. When the canvas is disabled (CANVAS_PROVIDER_TYPE != duckdb) the tool returns a capped inline preview with spilled=false and canvas_id empty; the SQL path is then unavailable. Supply exactly one of gene, transcript_id, or region. Echoes the effective dataset and build.\nData source: gnomAD (Broad Institute) — https://gnomad.broadinstitute.org/

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.

Drop a named table from a canvas to reclaim memory. Opt-in and off by default — a deliberate mutation on the otherwise read-only research surface. Use the canvas_id and table_name from a prior staging call. Per-table TTL already reclaims memory automatically, so this is a convenience for operators who want manual control.

Fetch gnomAD sequencing-coverage summary across a gene, transcript, or region — mean and median read depth, plus the mean fraction of samples covered at each depth threshold (1× through 100×), separated by exome and genome track. Use this to disambiguate a true absent variant from an uncallable position: a variant missing from a well-covered region is informative, while one missing from a poorly-covered region is not. Supply exactly one of gene, transcript_id, or region. The optional coverage_source narrows to one track; by default both available tracks are returned. Echoes the effective dataset and build.\nData source: gnomAD (Broad Institute) — https://gnomad.broadinstitute.org/

Run a read-only SQL SELECT against a canvas table staged by gnomad_list_gene_variants (table gene_variants) or gnomad_search_clinvar (table clinvar_variants). Use the canvas_id and table_name those tools returned to rank by allele frequency, group by consequence class, count loss-of-function variants, or filter the full set the inline preview only sampled. SELECT statements only — writes, DDL, and file/HTTP table functions are rejected by the canvas gate. Call gnomad_dataframe_describe first to discover staged table and column names.

Fetch gnomAD loss-of-function constraint for a gene — pLI (probability of LoF intolerance; >0.9 intolerant), LOEUF (oe_lof_upper, the headline metric; <0.6 intolerant in v4, <0.35 in v2) plus its lower bound, observed/expected ratios for LoF, missense, and synonymous variation, and the three Z-scores. This is the orthogonal axis to allele frequency: a loss-of-function variant matters far more in a gene intolerant to being broken. Accepts an HGNC symbol (PCSK9) or an Ensembl gene ID (ENSG00000169174). Many genes have null constraint (sparse upstream) — null fields are reported as such, never fabricated. v4 constraint is flagged beta by the gnomAD team; constraint_flags surfaces any caveats. Echoes the effective dataset and reference build.\nData source: gnomAD (Broad Institute) — https://gnomad.broadinstitute.org/

List the tables staged on a canvas and their columns (name and type) so you can write correct SQL for gnomad_dataframe_query. Use the canvas_id returned by gnomad_list_gene_variants or gnomad_search_clinvar. Returns one entry per table with its row count and column schema.