MCP serverai.genomicintelligence/genomic-intelligence
Hosted DNA language models: promoter, splice, enhancer, chromatin, expression, annotation
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
| Tool | Schema |
|---|---|
| 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 |
Verify it yourself
npx teppi-check https://mcp.genomicintelligence.ai/mcpcurl -s https://api.teppi.xyz/v1/trust/mcp/mcs_01M1FZ224DBBDPBDM9JKAD0PPX