Endpoints: 28,729MCP servers: 18,413Payout addresses: 2,070Paid calls: 1,518Letters: 13Defects: 1,321counted 2 min ago
teppi

MCP serverai.genomicintelligence/genomic-intelligence

Hosted DNA language models: promoter, splice, enhancer, chromatin, expression, annotation
UNRATEDActivestreamable-httpmcp.genomicintelligence.ai

Overview

Score?
UNRATED 0.681
of what a free look can see, on 32 looks
Looks
36
last 7 hr ago
Tools
15
changed 7 hr ago

More info

URL
mcp.genomicintelligence.ai/mcp
streamable-http
Says it is
gi-mcp 0.1.0a24
protocol 2025-06-18
In the record since
32 days ago

Among servers18,413 with a card

0median 0.606 · this server 0.681 · highest on record 0.8561

Toolsfrom sha256:55a6427d0a…6c239f · +0 −0 7 hr ago

The tools this server lists, read out of the definition it returned
ToolSchema
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 st
input · output
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
input · output
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 t
input · output
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
input · output
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
input · output
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.
input · output
list_jobs
List the caller's recent async jobs (also available as gi://jobs/recent).
input · output
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
input · output
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
input · output
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 padde
input · output
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: e
input · output
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')
input · output
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 t
input · output
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
input · output
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 c
input · output
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