Gget
davila7/claude-code-templates
CLI/Python toolkit for rapid bioinformatics queries. An agent skill from davila7/claude-code-templates.
Retrieve protein sequences and functional information from UniProt database by protein name, enabling protein analysis and bioinformatics workflows.
$ npx skills add InternScience/scp --skill uniprot-protein-retrieval -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install InternScience/scp uniprot-protein-retrieval --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/InternScience/scp.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/uniprot-protein-retrieval .claude/skills/uniprot-protein-retrieval && rm -rf skills-srcUse ~/.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/
Install the "uniprot-protein-retrieval" agent skill from https://github.com/InternScience/scp/tree/main/skills/uniprot-protein-retrieval into .claude/skills/uniprot-protein-retrieval/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "uniprot-protein-retrieval", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/InternScience/scp/tree/main/skills/uniprot-protein-retrievalType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add InternScience/scp --skill uniprot-protein-retrieval -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install InternScience/scp uniprot-protein-retrieval --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/InternScience/scp.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/uniprot-protein-retrieval .agents/skills/uniprot-protein-retrieval && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "uniprot-protein-retrieval" agent skill from https://github.com/InternScience/scp/tree/main/skills/uniprot-protein-retrieval into .agents/skills/uniprot-protein-retrieval/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "uniprot-protein-retrieval", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add InternScience/scp --skill uniprot-protein-retrieval -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install InternScience/scp uniprot-protein-retrieval --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/InternScience/scp.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/uniprot-protein-retrieval .cursor/skills/uniprot-protein-retrieval && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "uniprot-protein-retrieval" agent skill from https://github.com/InternScience/scp/tree/main/skills/uniprot-protein-retrieval into .cursor/skills/uniprot-protein-retrieval/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "uniprot-protein-retrieval", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/InternScience/scp.git --path skills/uniprot-protein-retrieval--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add InternScience/scp --skill uniprot-protein-retrieval -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install InternScience/scp uniprot-protein-retrieval --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/InternScience/scp.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/uniprot-protein-retrieval .gemini/skills/uniprot-protein-retrieval && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "uniprot-protein-retrieval" agent skill from https://github.com/InternScience/scp/tree/main/skills/uniprot-protein-retrieval into .gemini/skills/uniprot-protein-retrieval/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "uniprot-protein-retrieval", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install InternScience/scp uniprot-protein-retrievalInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add InternScience/scp --skill uniprot-protein-retrieval -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/InternScience/scp.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/uniprot-protein-retrieval .github/skills/uniprot-protein-retrieval && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "uniprot-protein-retrieval" agent skill from https://github.com/InternScience/scp/tree/main/skills/uniprot-protein-retrieval into .github/skills/uniprot-protein-retrieval/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "uniprot-protein-retrieval", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add InternScience/scp --skill uniprot-protein-retrieval -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install InternScience/scp uniprot-protein-retrieval --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/InternScience/scp.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/uniprot-protein-retrieval .opencode/skills/uniprot-protein-retrieval && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "uniprot-protein-retrieval" agent skill from https://github.com/InternScience/scp/tree/main/skills/uniprot-protein-retrieval into .opencode/skills/uniprot-protein-retrieval/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "uniprot-protein-retrieval", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
uniprot-protein-retrievalRetrieve protein sequences and functional information from UniProt database by protein name, enabling protein analysis and bioinformatics workflows.
Uniprot Protein Retrieval is an agent skill from InternScience/scp. Retrieve protein sequences and functional information from UniProt database by protein name, enabling protein analysis and bioinformatics workflows.
Its SKILL.md is about 2k 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 and Bioinformatics. It works with UniProt. The licence is MIT.
2 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit cea5398. It shows what the files ask for, not the result of running them.
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.
No scripts in the folder and no shell commands in SKILL.md (its code samples are python).
From the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Uniprot Protein Retrieval loads about 2k tokens when it runs. Until then it costs about 44 tokens; SKILL.md has 333 words of instructions outside code blocks.
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.
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.
The full file from InternScience/scp at commit cea5398, republished under its MIT licence (© InternScience). 333 words, ~2,025 tokens.
.claude/skills/uniprot-protein-retrieval/SKILL.md (or your agent's skills folder).Use the standard MCP client pattern for Origene-UniProt server.
This workflow retrieves protein sequences and associated information from the UniProt database using protein names or identifiers.
Workflow Steps:
Implementation:
from mcp.client.streamable_http import streamablehttp_client
from mcp import ClientSession
import json
class OrigeneClient:
def __init__(self, server_url: str):
self.server_url = server_url
self.session = None
async def connect(self):
try:
self.transport = streamablehttp_client(
url=self.server_url,
headers={"SCP-HUB-API-KEY": "<your-api-key>"}
)
self.read, self.write, self.get_session_id = await self.transport.__aenter__()
self.session_ctx = ClientSession(self.read, self.write)
self.session = await self.session_ctx.__aenter__()
await self.session.initialize()
print("✓ Connected to Origene-UniProt")
return True
except Exception as e:
print(f"✗ Connection failed: {e}")
return False
async def disconnect(self):
try:
if self.session:
await self.session_ctx.__aexit__(None, None, None)
if hasattr(self, 'transport'):
await self.transport.__aexit__(None, None, None)
print("✓ Disconnected")
except Exception as e:
print(f"✗ Disconnect error: {e}")
def parse_result(self, result):
try:
if hasattr(result, 'content') and result.content:
content = result.content[0]
if hasattr(content, 'text'):
return json.loads(content.text)
return str(result)
except Exception as e:
return {"error": f"Parse error: {e}", "raw": str(result)}
## Initialize client
client = OrigeneClient("https://scp.intern-ai.org.cn/api/v1/mcp/10/Origene-UniProt")
if not await client.connect():
print("Connection failed")
return
## Step 1: Retrieve protein sequence by name
protein_name = "insulin" # Can be common name, gene symbol, or UniProt ID
result = await client.session.call_tool(
"get_protein_sequence_by_name",
arguments={
"protein_name": protein_name
}
)
result_data = client.parse_result(result)
## Display results
print(f"\nProtein: {protein_name}")
print("=" * 80)
if "sequence" in result_data:
sequence = result_data["sequence"]
print(f"Amino Acid Sequence ({len(sequence)} residues):")
print(sequence)
# Format sequence in blocks of 60
print("\nFormatted Sequence:")
for i in range(0, len(sequence), 60):
position = i + 1
block = sequence[i:i+60]
print(f"{position:6d} {block}")
if "uniprot_id" in result_data:
print(f"\nUniProt ID: {result_data['uniprot_id']}")
if "protein_names" in result_data:
print(f"Protein Names: {result_data['protein_names']}")
if "organism" in result_data:
print(f"Organism: {result_data['organism']}")
if "function" in result_data:
print(f"Function: {result_data['function'][:200]}...")
await client.disconnect()## Retrieve multiple proteins
protein_list = ["p53", "BRCA1", "insulin", "hemoglobin"]
sequences = {}
for protein in protein_list:
result = await client.session.call_tool(
"get_protein_sequence_by_name",
arguments={"protein_name": protein}
)
data = client.parse_result(result)
if "sequence" in data:
sequences[protein] = {
"sequence": data["sequence"],
"length": len(data["sequence"]),
"uniprot_id": data.get("uniprot_id", "N/A")
}
## Display summary
print("\nProtein Sequence Summary:")
print(f"{'Protein':<15} {'UniProt ID':<12} {'Length':<10}")
print("-" * 40)
for name, info in sequences.items():
print(f"{name:<15} {info['uniprot_id']:<12} {info['length']:<10}")Origene-UniProt Server:
get_protein_sequence_by_name: Retrieve protein sequence from UniProt databaseprotein_name (str): Protein common name, gene symbol, or UniProt IDsequence (str): Amino acid sequence (one-letter code)uniprot_id (str): UniProt accession numberprotein_names (str): Official and alternative protein namesorganism (str): Source organismfunction (str): Protein function descriptionlength (int): Sequence length in residuesmass (float): Molecular mass (Da)Input:
protein_name: Protein identifier (flexible format)Output:
Use retrieved sequences for:
Combine with:
## 1. Retrieve sequence
result = await uniprot_client.session.call_tool(
"get_protein_sequence_by_name",
arguments={"protein_name": "BRCA1"}
)
sequence = uniprot_client.parse_result(result)["sequence"]
## 2. Find similar proteins (BLAST)
result = await biotools_client.session.call_tool(
"blast_search",
arguments={
"sequence": sequence,
"evalue": 1e-10,
"max_hits": 20
}
)
homologs = biotools_client.parse_result(result)
## 3. Identify domains (InterProScan)
result = await biotools_client.session.call_tool(
"interproscan_analyze",
arguments={
"sequence": sequence,
"databases": ["Pfam", "SMART"]
}
)
domains = biotools_client.parse_result(result)
## 4. Get disease associations (OpenTargets)
result = await opentargets_client.session.call_tool(
"get_target_associated_diseases",
arguments={"gene_symbol": "BRCA1"}
)
diseases = opentargets_client.parse_result(result)
print(f"Complete analysis for BRCA1:")
print(f"- Sequence length: {len(sequence)} amino acids")
print(f"- Homologs found: {len(homologs)}")
print(f"- Functional domains: {len(domains)}")
print(f"- Associated diseases: {len(diseases)}")Common issues:
© InternScience, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Just SKILL.md in skills/uniprot-protein-retrieval of InternScience/scp.
Open the folder on GitHubat commit cea5398
We found 2 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in InternScience/scp, which our catalogue first saw on October 7, 2026.
Uniprot Protein Retrieval 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.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Uniprot Protein Retrieval this skillInternScience/scp | 170 | 1 repos | ~2k | Automated safety check: Pass | MIT | |
| Ggetdavila7/claude-code-templates | 33k | 10 repos | ~6.3k | Automated safety check: Pass | MIT | |
| Tooluniverseynulihao/AgentSkillOS | 618 | 2 repos | ~2.5k | Automated safety check: Pass | None | |
| Ggetaipoch/medical-research-skills | 1.9k | — | ~816 | Automated safety check: Pass | MIT | |
| Uniprot Protein Databasejaechang-hits/SciAgent-Skills | 374 | 1 repos | ~3.4k | Automated safety check: Pass | CC-BY-4.0 | |
| Alphafold Database Fetch And Analyzegoogle-deepmind/science-skills | 3.2k | 2 repos | ~1.2k | Automated safety check: Pass | Apache-2.0 |
davila7/claude-code-templates
CLI/Python toolkit for rapid bioinformatics queries. An agent skill from davila7/claude-code-templates.
ynulihao/AgentSkillOS
A skill your agent uses when working with scientific research tools and workflows across bioinformatics, cheminformatics, genomics, structural biology, proteomics, and drug discovery.
aipoch/medical-research-skills
Unified CLI/Python interface for querying genomic, proteomic, structure, and expression data across 20+ bioinformatics databases; use when you need fast, scriptable retrieval by gene/protein IDs or…
jaechang-hits/SciAgent-Skills
Query UniProt REST API: search by gene/protein name, fetch FASTA, map IDs (Ensembl, PDB, RefSeq), access Swiss-Prot annotations.
google-deepmind/science-skills
Retrieve and analyze AlphaFold predicted structures for a protein.
aws-samples/amazon-bedrock-agents-healthcare-lifesciences
A skill your agent uses when a researcher needs to query biomedical databases for biomarker discovery, build target profiles from UniProt/Open Targets/STRING, rank biomarker candidates by evidence…
InternScience/scp
Given an rsID, query multiple databases (dbSNP, FAVOR, GWAS Catalog, ClinVar, gnomAD, PharmGKB, ClinGen) for comprehensive annotation.
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Calculate atmospheric parameters including Coriolis parameter, geostrophic wind, heat index, potential temperature, and dewpoint for meteorology and climate science.
InternScience/scp
Search biomedical literature and web content using Tavily search engine for research and clinical information.
InternScience/scp
Calculate buoyancy forces and acceleration for fluid mechanics and hydrodynamics analysis.
InternScience/scp
Calculate electrical capacitance from geometric parameters and dielectric properties for circuit design.
InternScience/scp
Search ChEMBL database for molecule information by name to retrieve bioactivity data and chemical structures.
Works with
Categories
Retrieve protein sequences and functional information from UniProt database by protein name, enabling protein analysis and bioinformatics workflows. Uniprot Protein Retrieval is an agent skill from InternScience/scp. Retrieve protein sequences and functional information from UniProt database by protein name, enabling protein analysis and bioinformatics workflows.
Uniprot Protein Retrieval fits situations like: tasks that involve Protein structure and design; tasks that involve Bioinformatics.
Run `npx skills add InternScience/scp --skill uniprot-protein-retrieval -a claude-code`. Or copy the skill folder (skills/uniprot-protein-retrieval in InternScience/scp) into .claude/skills/uniprot-protein-retrieval in your project. Claude Code loads it when a task matches its description.
Run `npx skills add InternScience/scp --skill uniprot-protein-retrieval -a codex`. Or copy the skill folder (skills/uniprot-protein-retrieval in InternScience/scp) into .agents/skills/uniprot-protein-retrieval in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add InternScience/scp --skill uniprot-protein-retrieval -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-protein-retrieval, .gemini/skills/uniprot-protein-retrieval, .github/skills/uniprot-protein-retrieval and .opencode/skills/uniprot-protein-retrieval in your project.
SKILL.md names no scripts, command-line tools or credentials: Uniprot Protein Retrieval is instructions for the agent only. Our summary lists: Python 3.
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
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.
Uniprot Protein Retrieval is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.
About 2k tokens (SKILL.md is roughly 8.1k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with Uniprot Protein Retrieval: Gget (davila7/claude-code-templates, 33k stars), Tooluniverse (ynulihao/AgentSkillOS, 618 stars), Gget (aipoch/medical-research-skills, 1.9k stars) and Uniprot Protein Database (jaechang-hits/SciAgent-Skills, 374 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
InternScience (a GitHub organization) maintains it in InternScience/scp, which has 170 GitHub stars. The repository holds 73 skills in this directory. The repository was last updated on June 3, 2026.
Source: InternScience/scp on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.