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Ncbi Sequence Fetch

Google DeepMindOfficialPublished by Google DeepMind

  • Skill
  • Tool integration
  • Science and research
  • Apache-2.0
  • Low risk
  • Has scripts

From the author

Retrieve protein and nucleotide sequences from NCBI databases using E-utilities. Supports direct accession lookup, CDS translation, gene+organism search, locus lookup, PubMed-linked sequences, patent protein extraction, and organism+length fallback search. Use when you need to fetch biological sequences by accession, gene name, locus tag, PubMed ID, or patent number.
— the description by Google DeepMind

AutoGineer summary

Written by AutoGineer from the skill’s own files, not by the author

The ncbi-sequence-fetch skill provides a structured interface to NCBI's Entrez E-utilities for retrieving biological sequence data. It supports multiple retrieval methods including direct accession lookups, CDS translation, gene and locus-based searches, PubMed-linked sequence extraction, and patent sequence retrieval. The tool outputs structured JSON data and includes a fallback mechanism for searching by organism and sequence length.

What it does

  • Fetches protein and nucleotide sequences by accession number.
  • Translates CDS and nucleotide records into protein sequences.
  • Searches NCBI databases using gene names, locus tags, or free-text queries.
  • Extracts protein sequences linked to specific PubMed articles.
  • Retrieves sequences from patent records using patent numbers or keywords.
  • Performs organism-based searches filtered by sequence length.

When to use it

  • When you need to obtain protein or nucleotide FASTA data from NCBI.
  • When you have a gene name or locus tag but lack a direct accession number.
  • When you need to extract sequences associated with a specific research publication.
  • When you need to retrieve sequences cited in patent documentation.
  • When you need to translate nucleotide CDS records into protein sequences.

Advantages

  • Automates complex E-utility workflows into simple command-line subcommands.
  • Provides consistent JSON output for downstream data processing.
  • Includes built-in rate limit management for NCBI API interactions.
  • Supports a wide range of search strategies from direct lookups to last-resort length matching.

Usage examples

“Fetch the protein sequence for accession XP_022033624.”
The tool retrieves the protein FASTA record and saves it as a JSON file.
“Find proteins linked to PubMed ID 24896089.”
The tool follows the link from the PubMed article to the associated protein records and returns the sequences.
“Search for the WRR4B gene in Arabidopsis thaliana.”
The tool queries the NCBI Protein database and returns matching sequences for the specified gene and organism.
“Translate the nucleotide sequence MK034466 to protein.”
The tool fetches the record and performs a CDS translation, returning the resulting protein sequence.

Install

  1. Download the skill as a ZIP:

    https://autogineer.com/agent-skills/google-deepmind/ncbi-sequence-fetch/download
  2. Unzip it into the cross-client skills folder of your project:

    mkdir -p .agents/skills && unzip ncbi-sequence-fetch.zip -d .agents/skills

Documentation by Google DeepMind

NCBI Sequence Fetch

Prerequisites

  1. uv: Read the uv skill and follow its Setup instructions to ensure uv is installed and on PATH.

  2. User Notification: If .licenses/ncbi_sequence_fetch_LICENSE.txt does not already exist in the workspace root directory then (1) prominently notify the user to check the terms at https://www.ncbi.nlm.nih.gov/ and https://www.ncbi.nlm.nih.gov/home/about/policies/, then (2) create the file recording the notification text and timestamp.

  3. .env file: Make sure the .env file exists in your home directory. Create one if it does not exist.

  4. NCBI_API_KEY (optional): Raises the NCBI rate limit from 3 to 10 requests/second. The skill works without it, but a key is recommended if the user plans many queries or encounters a 429 error. You can register for a key for free at https://www.ncbi.nlm.nih.gov/account/settings/. You MUST use the safe credentials protocol in the credentials skill to check for and request this key if this skill looks relevant to the user's request.

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.

  • API Key Support: If the user provides an NCBI_API_KEY in their environment, the query speed limits are automatically increased significantly.

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

Overview

Wraps NCBI's Entrez E-utilities (efetch, esearch, elink, esummary) for retrieving protein and nucleotide sequences. Provides 10 subcommands covering the full range of sequence retrieval workflows:

  • fetch-protein — Direct protein accession lookup (GenPept, RefSeq)

  • fetch-nucleotide — Direct nucleotide accession lookup

  • cds-translate — Fetch CDS and translate to protein (3 methods)

  • search — Free-text search of any NCBI database

  • elink — Follow cross-database links (PubMed→Protein, etc.)

  • gene-protein — Search protein by gene name + organism

  • locus-protein — Search protein by locus tag + organism

  • pubmed-proteins — Find proteins linked to a PubMed article

  • patent-search — Extract protein sequences from patents

  • organism-length — Last-resort search by organism + exact AA length

Utility Scripts

scripts/ncbi_fetch.py — Single script with subcommands.

All subcommands write structured JSON output. Use --output FILE to save to a file, or omit it to print to stdout. A human-readable summary is always printed to stdout.

1. Fetch Protein by Accession

Fetches protein FASTA from NCBI by accession (XP_, NP_, GenPept, etc.)

uv run scripts/ncbi_fetch.py fetch-protein XP_022033624 -o /tmp/result.json
uv run scripts/ncbi_fetch.py fetch-protein NP_001234567 ABC12345.1
2. Fetch Nucleotide by Accession

Fetches nucleotide FASTA from NCBI by accession.

uv run scripts/ncbi_fetch.py fetch-nucleotide MK034466 -o /tmp/result.json
3. CDS Translate

Fetches a CDS/nucleotide accession and translates to protein sequence. Tries three approaches in order: 1. NCBI's pre-translated CDS protein (fasta_cds_aa)

  1. GenBank XML CDS annotation translations 3. Raw nucleotide → 6-frame ORF finding

uv run scripts/ncbi_fetch.py cds-translate MK034466 -o /tmp/result.json
uv run scripts/ncbi_fetch.py cds-translate HQ662330 --target-length 1043

If the accession is a genomic record (not mRNA/CDS), the tool will report is_genomic: true so you can fall back to a homology-based approach instead.

4. Search Any Database

Free-text search using Entrez query syntax. Supports all NCBI databases.

# Search protein database
uv run scripts/ncbi_fetch.py search "WRR4B[Gene Name] AND Arabidopsis[Organism]" \
  --database protein --retmax 5 --fetch-sequences

# Search nucleotide database
uv run scripts/ncbi_fetch.py search "Rz2[Gene Name] AND Beta vulgaris[Organism]" \
  --database nuccore --retmax 10

# Search with patent filter
uv run scripts/ncbi_fetch.py search "disease resistance AND Solanum[Organism] AND patent[Properties]" \
  --database protein --fetch-sequences

# Search by sequence length
uv run scripts/ncbi_fetch.py search '"Oryza sativa"[Organism] AND 1043[SLEN]' \
  --database protein --fetch-sequences --retmax 50

Follow NCBI's cross-database links (e.g., PubMed article → linked proteins).

uv run scripts/ncbi_fetch.py elink 24896089 --dbfrom pubmed --db protein \
  --fetch-sequences -o /tmp/linked.json

Searches for protein sequences by gene name and organism. Searches NCBI Protein with [Gene Name] and [Organism] qualifiers.

uv run scripts/ncbi_fetch.py gene-protein WRR4B --organism "Arabidopsis thaliana"
uv run scripts/ncbi_fetch.py gene-protein Pikh-2 --organism "Oryza sativa" \
  --target-length 1043 -o /tmp/result.json

Searches by locus tag in both NCBI Protein and Nuccore databases. Extracts CDS translations from GenBank XML when direct protein hits aren't available.

uv run scripts/ncbi_fetch.py locus-protein At1g56540 --organism "Arabidopsis thaliana"
uv run scripts/ncbi_fetch.py locus-protein Niben101Scf02422g02015.1 \
  --organism "Nicotiana benthamiana" -o /tmp/result.json
8. PubMed-Linked Proteins

Finds protein sequences linked to a PubMed article. Searches NCBI Protein by PMID, follows elink PubMed→Protein, and extracts CDS translations from linked Nuccore records.

uv run scripts/ncbi_fetch.py pubmed-proteins 30692254 --identifier WRR4B
uv run scripts/ncbi_fetch.py pubmed-proteins 24896089 --identifier "K2" \
  -o /tmp/result.json

Two modes:

By patent number — fetches all protein sequences from a specific patent: bash uv run scripts/ncbi_fetch.py patent-search --patent-number US10123456 -o /tmp/patent.json

By keywords — searches NCBI Protein with patent[Properties] filter: bash uv run scripts/ncbi_fetch.py patent-search --keywords WRR4B Albugo --organism "Arabidopsis thaliana" -o /tmp/patent.json

[!IMPORTANT] Patent convention: In molecular biology patents, SEQ ID NO: 1 is typically the DNA sequence and SEQ ID NO: 2 is the primary protein. Higher SEQ ID NOs are variants or related sequences. Prefer Sequence 2 when selecting the primary protein of interest.

Last-resort search when only organism and expected protein length are known. Uses NCBI's [SLEN] filter for exact length matching.

uv run scripts/ncbi_fetch.py organism-length \
  --organism "Arabidopsis thaliana" --length 1048 --retmax 50 \
  -o /tmp/result.json

[!NOTE] This often returns multiple candidates. Use the JSON output headers to identify the correct protein.

Workflow

Standard Sequence Retrieval Cascade

When trying to find a protein sequence, follow this priority order:

  1. Direct accession — fetch-protein with GenPept/RefSeq accession

  2. CDS translation — cds-translate with nucleotide/CDS accession

  3. PubMed-linked — pubmed-proteins with PMID + gene name

  4. Locus lookup — locus-protein with locus tag + organism

  5. Gene + organism — gene-protein with gene name + organism

  6. Patent search — patent-search with patent number or keywords

  7. Organism + length — organism-length as last resort

Interpreting Results
  • All subcommands return JSON with a results array

  • Each result has sequence (AA string), length, and header/metadata

  • When multiple results are returned, select by:

    • Closest match to expected length (target_length)

    • Header relevance (matching gene name, "disease resistance" keywords)

    • Source priority (RefSeq > GenPept > patent)

Reference

  • NCBI E-utilities docs: https://www.ncbi.nlm.nih.gov/books/NBK25499/

  • Entrez search syntax: https://www.ncbi.nlm.nih.gov/books/NBK49540/

  • Database list: protein, nuccore, gene, pubmed, pmc, biosample, etc.

  • Common accession formats:

    • XP_ / NP_ — NCBI RefSeq protein

    • AAA to AZZ + digits — GenPept (translated GenBank)

    • MK, MN, HQ, etc. + digits — GenBank nucleotide

    • ENSG, ENST, ENSP — Ensembl (use ensembl-database skill instead)

    • Q, P, O + digits — UniProt (use uniprot-database skill instead)

Files

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Requirements and compatibility

Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta

“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.

Needs: Needs an API key, Needs Python

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Attribution and licence

Published by
Google DeepMind
Publisher
Google DeepMind (Official)
Source
google-deepmind/science-skills · skills/ncbi_sequence_fetch · commit 4de6786
Licence
Apache License 2.0 (redistribution allowed)
  • LICENSE (added by AutoGineer from LICENSE)
  • ATTRIBUTION.md (written by AutoGineer)
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