Access UniProt for protein sequence and annotation retrieval.

MITAuto-check passedResearch & Science

Install Uniprot

skills CLI
$ npx skills add adaptyvbio/protein-design-skills --skill uniprot -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install adaptyvbio/protein-design-skills uniprot --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/adaptyvbio/protein-design-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/uniprot .claude/skills/uniprot && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
uniprot
GitHub stars
164
Used in
2 other repos
Token cost
~1.3k tokens
SKILL.md length
107 words
Files
1
Skills in repo
24
Repo updated
First seen
Licence
MIT

At a glance

Access UniProt for protein sequence and annotation retrieval.

  • Looking up protein sequences by accession
  • SKILL.md covers Fetching Sequences, Getting Annotations, Searching UniProt and Cross-References, plus 3 more sections
  • Calls curl; reaches rest.uniprot.org and uniprot.org
  • Finding functional annotations

What it does

Uniprot is an agent skill from adaptyvbio/protein-design-skills. Access UniProt for protein sequence and annotation retrieval. Use this skill when: (1) Looking up protein sequences by accession, (2) Finding functional annotations, (3) Getting domain boundaries, (4) Finding homologs and variants, (5) Cross-referencing to PDB structures. For structure retrieval, use pdb. For sequence design, use proteinmpnn.

Its SKILL.md is about 1.3k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Research & Science, covering Protein structure and design. It works with UniProt. The repository describes itself as: Claude Code skills for protein design. The licence is MIT.

When your agent uses it

  • Looking up protein sequences by accession
  • Finding functional annotations
  • Getting domain boundaries
  • Finding homologs and variants

Example prompts

  • “/uniprot”

Requirements

  • Python 3

What it can do on your machine

Read from SKILL.md and the folder at commit 59dd633. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • curl

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Hosts in commands or code, which the agent is likely to contact:

    • rest.uniprot.org
    • uniprot.org

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Uniprot loads about 1.3k tokens when it runs. Until then it costs about 88 tokens; SKILL.md has 107 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~88
When it runs · the whole SKILL.md, loaded when a task matches
~1.3k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from adaptyvbio/protein-design-skills at commit 59dd633, republished under its MIT licence (© adaptyvbio). 107 words, ~1,268 tokens.

Download SKILL.mdSave it as .claude/skills/uniprot/SKILL.md (or your agent's skills folder).
name
uniprot
description
Access UniProt for protein sequence and annotation retrieval. Use this skill when: (1) Looking up protein sequences by accession, (2) Finding functional annotations, (3) Getting domain boundaries, (4) Finding homologs and variants, (5) Cross-referencing to PDB structures. For structure retrieval, use pdb. For sequence design, use proteinmpnn.
license
MIT
category
utilities
tags
database, sequence, annotation

UniProt Database Access

Note: This skill uses the UniProt REST API directly. No Modal deployment needed - all operations run locally via HTTP requests.

Fetching Sequences

By Accession
bash
# FASTA format
curl "https://rest.uniprot.org/uniprotkb/P00533.fasta"

# JSON format with annotations
curl "https://rest.uniprot.org/uniprotkb/P00533.json"
Using Python
python
import requests

def get_uniprot_sequence(accession):
    """Fetch sequence from UniProt."""
    url = f"https://rest.uniprot.org/uniprotkb/{accession}.fasta"
    response = requests.get(url)
    if response.ok:
        lines = response.text.strip().split('\n')
        header = lines[0]
        sequence = ''.join(lines[1:])
        return header, sequence
    return None, None

Getting Annotations

Full Entry
python
def get_uniprot_entry(accession):
    """Fetch full UniProt entry as JSON."""
    url = f"https://rest.uniprot.org/uniprotkb/{accession}.json"
    response = requests.get(url)
    return response.json() if response.ok else None

entry = get_uniprot_entry("P00533")
print(f"Protein: {entry['proteinDescription']['recommendedName']['fullName']['value']}")
Domain Boundaries
python
def get_domains(accession):
    """Extract domain annotations."""
    entry = get_uniprot_entry(accession)
    domains = []

    for feature in entry.get('features', []):
        if feature['type'] == 'Domain':
            domains.append({
                'name': feature.get('description', ''),
                'start': feature['location']['start']['value'],
                'end': feature['location']['end']['value']
            })

    return domains

# Example: EGFR domains
domains = get_domains("P00533")
# [{'name': 'Kinase', 'start': 712, 'end': 979}, ...]

Searching UniProt

By Gene Name
python
def search_uniprot(query, organism=None, limit=10):
    """Search UniProt by query."""
    url = "https://rest.uniprot.org/uniprotkb/search"
    params = {
        "query": query,
        "format": "json",
        "size": limit
    }
    if organism:
        params["query"] += f" AND organism_id:{organism}"

    response = requests.get(url, params=params)
    return response.json()['results']

# Search for human EGFR
results = search_uniprot("EGFR", organism=9606)
By Sequence Similarity (BLAST)
python
# Use UniProt BLAST
# https://www.uniprot.org/blast

Cross-References

Get PDB Structures
python
def get_pdb_references(accession):
    """Get PDB structures for UniProt entry."""
    entry = get_uniprot_entry(accession)
    pdbs = []

    for xref in entry.get('uniProtKBCrossReferences', []):
        if xref['database'] == 'PDB':
            pdbs.append({
                'pdb_id': xref['id'],
                'method': xref.get('properties', [{}])[0].get('value', ''),
                'chains': xref.get('properties', [{}])[1].get('value', '')
            })

    return pdbs

# Example: PDB structures for EGFR
pdbs = get_pdb_references("P00533")

Common Use Cases

Target Selection
python
# 1. Find protein by name
results = search_uniprot("insulin receptor", organism=9606)

# 2. Get accession
accession = results[0]['primaryAccession']  # e.g., P06213

# 3. Get domains
domains = get_domains(accession)

# 4. Find PDB structure
pdbs = get_pdb_references(accession)

# 5. Download best structure for design
Sequence Alignment Info
python
def get_sequence_variants(accession):
    """Get natural variants from UniProt."""
    entry = get_uniprot_entry(accession)
    variants = []

    for feature in entry.get('features', []):
        if feature['type'] == 'Natural variant':
            variants.append({
                'position': feature['location']['start']['value'],
                'original': feature.get('alternativeSequence', {}).get('originalSequence', ''),
                'variant': feature.get('alternativeSequence', {}).get('alternativeSequences', [''])[0],
                'description': feature.get('description', '')
            })

    return variants

API Reference

EndpointDescription
/uniprotkb/{id}.fastaFASTA sequence
/uniprotkb/{id}.jsonFull entry JSON
/uniprotkb/searchSearch entries
/uniprotkb/streamBatch download

Troubleshooting

Entry not found: Check accession format (e.g., P00533) Rate limits: Add delay between requests Large downloads: Use stream endpoint with pagination


Next: Use sequence with esm for embeddings or chai / boltz for structure.

© adaptyvbio, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/uniprot of adaptyvbio/protein-design-skills.

Open the folder on GitHubat commit 59dd633

Used in 2 other repositories

We found 2 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 2 other GitHub owners. This page covers the copy in adaptyvbio/protein-design-skills, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Uniprot next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Uniprot compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Uniprot this skilladaptyvbio/protein-design-skills1642 repos~1.3kAutomated safety check: PassMIT
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Bio DB ToolsDrugClaw/DrugClaw125—~1.4kAutomated safety check: PassApache-2.0
Ggetdavila7/claude-code-templates32k10 repos~6.3kAutomated safety check: PassMIT
Alphafold Databasedavila7/claude-code-templates32k10 repos~4kAutomated safety check: PassMIT
Uniprot Databasegoogle-deepmind/science-skills3.2k1 repos~3.1kAutomated safety check: PassApache-2.0

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Works with

Questions about Uniprot

What does Uniprot do?

Access UniProt for protein sequence and annotation retrieval. Uniprot is an agent skill from adaptyvbio/protein-design-skills. Access UniProt for protein sequence and annotation retrieval.

When should I use Uniprot?

Uniprot fits situations like: looking up protein sequences by accession; finding functional annotations; getting domain boundaries; finding homologs and variants.

How do I install Uniprot in Claude Code?

Run `npx skills add adaptyvbio/protein-design-skills --skill uniprot -a claude-code`. Or copy the skill folder (skills/uniprot in adaptyvbio/protein-design-skills) into .claude/skills/uniprot in your project. Claude Code loads it when a task matches its description.

How do I install Uniprot in Codex?

Run `npx skills add adaptyvbio/protein-design-skills --skill uniprot -a codex`. Or copy the skill folder (skills/uniprot in adaptyvbio/protein-design-skills) into .agents/skills/uniprot in your project. Codex loads it when a task matches its description.

Can I use Uniprot in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add adaptyvbio/protein-design-skills --skill uniprot -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/uniprot, .gemini/skills/uniprot, .github/skills/uniprot and .opencode/skills/uniprot in your project.

What does Uniprot need to run?

Going by SKILL.md and its folder, Uniprot needs the command-line tools its instructions call (curl). Our summary lists: Python 3.

Does Uniprot access the network?

SKILL.md names 2 domains. In commands or code: rest.uniprot.org and uniprot.org; the agent is likely to contact these when it follows the instructions. This is read from the text; nothing was executed.

Is Uniprot safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Uniprot use?

Uniprot is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Uniprot use?

About 1.3k tokens (SKILL.md is roughly 5.1k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Uniprot?

Skills that share tags, products or a category with Uniprot: Alphafold Database Fetch And Analyze (google-deepmind/science-skills, 3.2k stars), Bio DB Tools (DrugClaw/DrugClaw, 125 stars), Gget (davila7/claude-code-templates, 32k stars) and Alphafold Database (davila7/claude-code-templates, 32k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Uniprot?

adaptyvbio (a GitHub organization) maintains it in adaptyvbio/protein-design-skills, which has 164 GitHub stars. The repository holds 24 skills in this directory. The repository was last updated on June 11, 2026.

Source: adaptyvbio/protein-design-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.