mcpbeat

Query Interpro

biotender-max/query-interpro

Query InterPro for protein domains and families. Use when user asks about protein domains, functional sites, protein families, domain architecture, or motifs. Triggers on "interpro", "protein domain", "domain architecture", "protein family", "functional site", "motif".

703 tokens
context cost
the whole folder, loaded on every use
1
files
instructions only
0
copies elsewhere
how many repositories repackaged it
132
stars on the repo
on the repository, not the skill itself

Install

one command, takes just this skill from the repository
npx skills add https://github.com/BioTender-max/awesome-bio-agent-skills --skill query-interpro

The instruction itself

5 sections, as written by the author

InterPro Protein Domain Database

Query the InterPro REST API for protein domains, families, and functional sites.

When to Use

  • User asks about domains in a protein
  • User wants to know what family a protein belongs to
  • User asks about functional sites or motifs
  • User wants domain architecture visualization

How to Execute

import requests
import json

BASE_URL = "https://www.ebi.ac.uk/interpro/api"

# 1. Get protein annotation (domains/families for a UniProt ID)
def get_protein_domains(uniprot_id):
    url = f"{BASE_URL}/protein/uniprot/{uniprot_id}"
    r = requests.get(url, headers={"Accept": "application/json"})
    r.raise_for_status()
    return r.json()

# 2. Get InterPro entry details
def get_interpro_entry(interpro_id):
    url = f"{BASE_URL}/entry/interpro/{interpro_id}"
    r = requests.get(url, headers={"Accept": "application/json"})
    r.raise_for_status()
    return r.json()

# 3. Search InterPro by text
def search_interpro(query, max_results=10):
    url = f"{BASE_URL}/entry/interpro"
    params = {"search": query, "page_size": max_results}
    r = requests.get(url, params=params, headers={"Accept": "application/json"})
    r.raise_for_status()
    return r.json()

# 4. Get domain matches for a protein
def get_domain_matches(uniprot_id):
    url = f"{BASE_URL}/protein/uniprot/{uniprot_id}/entry/interpro"
    r = requests.get(url, headers={"Accept": "application/json"})
    r.raise_for_status()
    return r.json()

# Example: TP53 domains
domains = get_domain_matches("P04637")
for result in domains.get("results", []):
    meta = result.get("metadata", {})
    name = meta.get("name", "N/A")
    ipr_type = meta.get("type", "N/A")
    accession = meta.get("accession", "N/A")
    proteins = result.get("proteins", [])
    if proteins:
        locations = proteins[0].get("entry_protein_locations", [])
        for loc in locations:
            for frag in loc.get("fragments", []):
                start = frag.get("start", "?")
                end = frag.get("end", "?")
                print(f"{accession} ({ipr_type}): {name} [{start}-{end}]")

Entry Types

  • domain — Structural/functional domain
  • family — Protein family
  • homologous_superfamily — Distant homologs
  • repeat — Repeated motif
  • site — Active/binding site

Follow-up Suggestions

  • "Want me to compare domains across species?"
  • "Should I map these domains onto the 3D structure?"
  • "Want me to find other proteins with the same domain?"

How to use it

Copy the folder

Take biotender-max/query-interpro from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

Check the name does not clash

The agent identifies a skill by the name field in its header. Two skills with the same name cannot sit side by side — one of them will be ignored.