Genomic Intelligence
Hosted DNA language models: promoter, splice, enhancer, chromatin, expression, annotation
https://mcp.genomicintelligence.ai/mcpCurrent observation
This endpoint answered at its latest recorded check.
What this server reports about itself
Self-reported at initialize. Not verified by Licium.
- Server name
- gi-mcp
- Version
- 0.1.0a15
- Capability keys
- experimental, prompts, resources, tools
- Tool names
- list_models, fetch_ensembl_sequence, fetch_region, fetch_gene_for_expression, load_demo_sequence, store_inline_sequence, predict_promoter, predict_splice, predict_enhancer, predict_chromatin, predict_expression, find_genes, find_genes_and_predict_expression, get_job, list_jobs
Genomic Intelligence DNA analysis over MCP. Six inference tasks (promoter, splice, enhancer, chromatin, expression, annotation), plus a composite annotation→expression workflow. For research and development use, not clinical or diagnostic decisions. For high-volume or latency-sensitive use, contact contact@genomicintelligence.ai to provision a production-shaped deployment. Recommended flow to avoid bloating context with large sequences: 1. Acquire a sequence as a *handle* (fetch_ensembl_sequence, fetch_gene_for_expression, load_local_fasta, or store_inline_sequence). 2. Pass the returned `sequence_ref` to a predict_* tool. Small sequences may instead be passed inline via `sequence`. Reference context lives in resources: gi://models, gi://docs/tasks, gi://sequences, gi://account.
Reported Aug 17, 2026, 05:03 AM UTC.
Check history
Oldest to newest. Each row is one recorded check.
- respondsMCP initialize · 8s limit · HTTP 200 · 867ms
- respondsMCP initialize · 8s limit · HTTP 200 · 517ms
- respondsMCP initialize · 8s limit · HTTP 200 · 91ms
- respondsMCP initialize · 8s limit · HTTP 200 · 162ms