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Ensembl Database

  • 1.3k installs
  • 2.6k repo stars
  • Updated July 7, 2026
  • google-deepmind/science-skills

ensembl-database is a Claude Code skill that queries the Ensembl REST API for genomic and biological reference data for developers building bioinformatics pipelines or agent tools that need programmatic access to Ensembl

About

ensembl-database is a science skill from google-deepmind/science-skills providing a concise reference for the Ensembl REST API at https://rest.ensembl.org. The skill documents GRCh38 and GRCh37 endpoints (https://grch37.rest.ensembl.org), content negotiation headers for JSON, plain text, FASTA, and GFF3 responses, and a 15 requests per second rate limit. Developers reach for ensembl-database when the bundled ensembl_api.py script does not cover a specific genomic query and custom REST calls are needed. Use it in Claude, Cursor, or custom agents that fetch gene annotations, sequences, or variant data from Ensembl. The reference supports building bioinformatics integrations without manually parsing the full Ensembl API documentation.

  • Full reference for the Ensembl REST API including all lookup, overlap, sequence, and variation endpoints
  • Supports multiple content types: JSON, plain sequence, FASTA, and GFF3
  • Rate-limit guidance and retry handling for production agent use
  • Region format and query parameter conventions for reliable genomic queries
  • GRCh38 and GRCh37 endpoint support for different genome builds

Ensembl Database by the numbers

  • 1,270 all-time installs (skills.sh)
  • +166 installs in the week ending Aug 5, 2026 (Skillselion tracking)
  • Ranked #356 of 4,347 Backend & APIs skills by installs in the Skillselion catalog
  • Security screen: LOW risk (skills.sh audit)
  • Data as of Aug 5, 2026 (Skillselion catalog sync)
npx skills add https://github.com/google-deepmind/science-skills --skill ensembl-database

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Installs1.3k
repo stars2.6k
Security audit3 / 3 scanners passed
Last updatedJuly 7, 2026
Repositorygoogle-deepmind/science-skills

How do you query the Ensembl REST API for genomic data?

Query genomic databases and biological reference data directly from Claude, Cursor or custom agents.

Who is it for?

Bioinformatics developers and data engineers building genomic pipelines that need programmatic Ensembl REST API access beyond bundled script coverage.

Skip if: Clinical diagnostic workflows requiring certified pipelines, non-genomic general database queries, or teams with no need for Ensembl reference data.

When should I use this skill?

A developer asks to query Ensembl, fetch genomic annotations, build custom Ensembl REST calls, or integrate biological reference data into an agent pipeline.

What you get

Custom Ensembl REST API queries returning JSON, FASTA, GFF3, or plain-text genomic reference data.

  • Custom Ensembl API queries
  • Genomic annotation data
  • Sequence exports in FASTA or GFF3

By the numbers

  • Ensembl REST API rate limit of 15 requests per second
  • Supports GRCh38 and GRCh37 genome builds via separate base URLs

Files

SKILL.mdMarkdownGitHub ↗

Ensembl Database: ID Mapping and Genomic Features

Prerequisites

1. `uv`: Read the uv skill and follow its Setup instructions to ensure uv is installed and on PATH. 2. User Notification: If LICENSE_NOTIFICATION.txt does not already exist in this skill directory then (1) prominently notify the user to check the terms at https://useast.ensembl.org/index.html and https://github.com/Ensembl/ensembl-rest/wiki, then (2) create the file recording the notification text and timestamp.

Overview

The Ensembl database is a resource for genome annotation. This skill allows you to interact with the Ensembl REST API to resolve ambiguous symbols, cross-reference IDs (RefSeq, HGNC, UniProt, ENSG), fetch raw sequences, and retrieve detailed transcript structures.

Key Concepts:

  • ENSG (Gene): Stable identifier for a human gene. Other species will have

different three-letter species codes.

  • ENST (Transcript): Stable identifier for a transcript (splicing

isoform).

  • ENSP (Protein): Stable identifier for a translated protein.
  • MANE Select: The consensus primary transcript agreed upon by Ensembl and

NCBI.

  • Canonical: Ensembl's representative transcript (used if MANE is not

available or non-human).

Core Rules

  • Use the Wrapper: ALWAYS execute the provided helper scripts to query the

database rather than accessing the database directly. The scripts automatically enforce the required rate limit gracefully.

  • Default Species: If the species is absent or ambiguous in the prompt,

default to "human". You MUST explicitly flag this default to the user to ensure they are aware.

  • Primary Transcripts: When listing transcripts for a gene, only return

the MANE Select transcript (for human) or the Canonical transcript (for others) unless the user explicitly asks for all alternative isoforms. You MUST flag to the user when multiple transcripts are available and you are defaulting to the primary one.

  • Assembly Handling: The default assembly is GRCh38. For GRCh37 requests,

you MUST use the --assembly GRCh37 flag. You MUST explicitly flag to the user when a non-default assembly is being used.

  • Output Location: The script writes full JSON/FASTA output to temporary

files in /tmp by default, or to a user-specified file using the --output flag. It also prints a concise summary to stdout.

  • Notification: If this skill is used, ensure this is mentioned in the

output.

Available Commands

1. Resolve Gene ID — Resolve a symbol, alias, or RefSeq ID to ENSG ID(s). Automatically falls back to resolving synonyms if primary symbol is not found.

uv run scripts/ensembl_api.py resolve-gene TP53 --species human --output tp53.json
uv run scripts/ensembl_api.py resolve-gene PCL2 --output pcl2.json # Falls back to synonym resolution

2. Map ID to External Database — Cross-reference an Ensembl ID to UniProt, HGNC, RefSeq, etc.

uv run scripts/ensembl_api.py map-id ENSG00000141510 --external-db UniProt --output uniprot_map.json
uv run scripts/ensembl_api.py map-id ENST00000269305 --external-db RefSeq_mRNA --output refseq_map.json

3. Get Genomic Sequence — Fetch raw DNA for a coordinate window. Supports GRCh37 via --assembly GRCh37.

uv run scripts/ensembl_api.py get-sequence 17:7661779-7687550 --species human --output seq.txt
uv run scripts/ensembl_api.py get-sequence chr9:21971100-21971200 --assembly GRCh37 --output seq_grch37.txt

4. Gene Summary — High-level metadata: symbol, biotype, description, chromosomal location.

uv run scripts/ensembl_api.py gene-summary ENSG00000141510 --output gene_summary.json

5. List Transcripts — All transcripts for a gene, with optional --only-mane or --only-canonical filters. Output includes Transcript Support Level (TSL).

uv run scripts/ensembl_api.py transcripts ENSG00000141510 --only-mane --output transcripts_mane.json
uv run scripts/ensembl_api.py transcripts ENSG00000141510 --only-canonical --output transcripts_canonical.json
uv run scripts/ensembl_api.py transcripts ENSG00000141510 --output transcripts_all.json

5b. Canonical TSS — Get the single coordinate of the Transcription Start Site (TSS) for the canonical transcript of a gene.

[!NOTE] Unlike the standard transcripts command, canonical-tss accepts
both symbols (e.g., TP53) and Ensembl IDs, and automatically resolves them.
It also does the math for strand orientation (TSS is Start for + strand
and End for - strand), outputting the single integer coordinate directly.
uv run scripts/ensembl_api.py canonical-tss TP53 --output tp53_tss.json
uv run scripts/ensembl_api.py canonical-tss ENSG00000141510 --output tss.json

6. Transcript Structure — Exon coordinates, CDS boundaries, and computed 5'/3' UTR regions for a transcript.

uv run scripts/ensembl_api.py transcript-structure ENST00000269305 --output structure.json

7. Protein Info — ENSP ID and sequence length for a transcript.

uv run scripts/ensembl_api.py protein-info ENST00000269305 --output protein_info.json

8. Protein Sequence — Amino acid FASTA for a transcript (ENST) or protein (ENSP) ID.

uv run scripts/ensembl_api.py protein-sequence ENST00000269305 --output protein.fasta
uv run scripts/ensembl_api.py protein-sequence ENSP00000269305 --output protein_ensp.fasta

9. Variant Consequence (VEP) — Predict molecular consequences for a genomic variant. Includes open-licensed plugins: AlphaMissense, Conservation, DosageSensitivity, IntAct, MaveDB, OpenTargets, LoF (Loftee), NMD, UTRAnnotator, mutfunc, LOEUF.

uv run scripts/ensembl_api.py vep 9:21971147:T:C --species human --output vep.json
uv run scripts/ensembl_api.py vep rs699 --species human --output vep_rs699.json

Example VEP stdout output:

[*] Variant: 9:21971147:T>C
[*] Most severe consequence: missense_variant
[*] Found 15 transcript consequences.

[*] VEP Predictions:

  - ENST00000304494 (CDKN2A): Consequence = missense_variant
  - ENST00000304494 (CDKN2A): Amino Acids = N/S
  - ENST00000304494 (CDKN2A): SIFT = deleterious (0.01)
  - ENST00000304494 (CDKN2A): AlphaMissense Class = likely_benign
  - ENST00000304494 (CDKN2A): AlphaMissense Pathogenicity = 0.2129
  - ENST00000304494 (CDKN2A): Conservation = 2.05
  - ENST00000304494 (CDKN2A): Dosage Sensitivity (Haplo) = 0.889228328567991
  - ENST00000304494 (CDKN2A): Dosage Sensitivity (Triplo) = 0.135514349094646
  - ENST00000304494 (CDKN2A): Loss of Function (LOEUF) = 0.791

Presenting VEP Results: After running the VEP command, you MUST present the full VEP Predictions list from stdout to the user. This list contains both standard VEP predictions (Consequence, Amino Acids, SIFT, PolyPhen) and open-license plugin results (AlphaMissense, Conservation, Dosage Sensitivity, LOEUF, Loftee LoF, NMD, UTRAnnotator, Mutfunc). Do NOT just summarize — show the complete list so the user can see all predictions. If the list is very long (many transcripts), show the MANE Select / canonical transcript rows in full and note that the complete data is in the JSON output.

Parsing Outputs

If the user needs detailed, nested structural data (like the precise integer coordinates of Exon 2 of a transcript) that isn't summarized in stdout:

1. Locate the JSON file (either specified via --output or the temporary file path printed by the script). 2. Use terminal tools like jq or write a quick, disposable python snippet to extract the specific data point requested. Do not attempt to read the entire JSON file into your context if it is very large.

Custom Queries

If you need to make an API call that the script does not support (e.g., fetching protein domain annotations, coordinate mapping between assemblies, homology searches, linkage disequilibrium, or phenotype lookups), read references/ensembl_rest_api_reference.md for a complete reference of available endpoints, parameters, and response fields.

CRITICAL: When writing custom scripts or using alternatives to the provided scripts, you MUST respect the Ensembl REST API rate limits (maximum 15 requests per second) and handle 429 Too Many Requests errors gracefully (e.g., with exponential backoff).

Related skills

FAQ

What is the Ensembl REST API rate limit?

ensembl-database documents a maximum of 15 requests per second for the Ensembl REST API at https://rest.ensembl.org. Exceeding this limit triggers HTTP rate-limit responses from the Ensembl service.

Which response formats does ensembl-database support?

ensembl-database covers Content-Type negotiation for application/json, text/plain raw sequences, text/x-fasta FASTA output, and text/x-gff3 GFF3 annotation responses from Ensembl REST endpoints.

Is Ensembl Database safe to install?

skills.sh reports 3 of 3 security scanners passed. Review the Security Audits panel on this page before installing in production.

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