Genomic Intelligence

Reliability

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How to connect

Add it to any MCP client that supports remote servers.

{
  "mcpServers": {
    "genomic-intelligence": {
      "type": "http",
      "url": "https://mcp.genomicintelligence.ai/mcp"
    }
  }
}

15 tools

• list_models

  List available models for a task. Use to discover model ids before passing one as the `model` argument to a predict tool. The same catalog is also available as the resource `gi://models`. Returns a FLAT object — {task, default_model, models…

• fetch_ensembl_sequence

  Fetch a gene's reference sequence from Ensembl and store it. Returns a handle ({ref, name, length, preview, ...}). Pass the `ref` to predict_* tools — the bases stay server-side. For expression, use fetch_gene_for_expression instead (it prepares…

• fetch_region

  Fetch a genomic region by coordinates from Ensembl and store it. For "find the genes in chr8:127,680,000-127,800,000"-style requests: resolves a coordinate range to reference sequence and returns a handle ({ref, name, length, ...}) to pass to find_genes…

• fetch_gene_for_expression

  Fetch a gene's sequence prepared for expression prediction. Resolves the gene's canonical-transcript TSS via Ensembl and stores a gene-sense sequence centred on it, as a handle to pass to predict_expression(sequence_ref=...). Longer TSS-centred sequence…

• load_demo_sequence

  Load a bundled demo reference sequence and return a handle. The server ships one curated, task-correct positive control per task (list them via the gi://sequences resource) — e.g. `expression_hbb_k562` is a ready-to-use K562 expression window for…

• store_inline_sequence

  Store a human-pasted sequence and return a handle to re-use it. For a sequence you've already pasted into the conversation, this gives back a short handle so you can run several tasks on it without re-pasting the bases in each predict_* call. Note that…

• predict_promoter

  Predict promoter regions (G0). 300–500,000 bp. Returns the {data, meta} envelope: data.regions lists predicted promoters with start/end/score. 300 bp is the task floor for every promoter model. The default g0-promoter-2000bp scans a 2,000 bp…

• predict_splice

  Predict splice donor/acceptor sites (G0 BigBird). 100–500,000 bp. The model reads a 15,000 bp context window, so anything shorter is scored against a padded window — feed a whole transcript locus when you can. It is also strand-specific, and the wrong…

• predict_enhancer

  Predict enhancer activity (G0 DeepSTARR). 50–500,000 bp. 50 bp is the task's admission floor (the API 422s below it), not a statement about what the model reads: enhancer models score a 249 bp context window, so 50–248 bp is accepted and scored against a…

• predict_chromatin

  Chromatin annotation across 919 features (G0 DeepSEA). 200–500,000 bp. The model reads a 1,000 bp context window; 200–999 bp is accepted and scored against a padded window.

• predict_expression

  Predict a gene's expression from the sequence around its TSS. Expression is cell-type-specific, so `description` (cell type / assay context, e.g. 'K562 cell line') is REQUIRED — the API rejects requests without it. The input rule is the same for…

• find_genes

  Find genes (transcript intervals) in a genomic region (async, ~8-25s). Takes 1,000–500,000 bp. The floor is the strictest of the scanning tasks: gene finding needs a region, not a site. (Only expression's 9,198 bp is higher, and that is the sequence…

• find_genes_and_predict_expression

  Find genes in a sequence, then predict each gene's expression (composite). Server-side chaining in ONE call: finds genes (transcript intervals, with their TSS) in the sequence, then predicts expression off each discovered TSS in the given experimental…

• get_job

  Poll an async job once. Returns the {data, meta} result if complete, a progress envelope if still running, or an error envelope if it failed.

• list_jobs

  List the caller's recent async jobs (also available as gi://jobs/recent).

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