bc_get_protein_domains
Retrieve detailed protein domain architecture and InterPro matches for functional insights. Input a protein ID to access domain information, optional structural details, and species-specific filtering. Use with UniProt ID for accurate results.
Instructions
Get domain architecture and InterPro matches for a specific protein.
This function retrieves all InterPro domain matches for a given protein, providing insight into the protein's functional domains and architecture.
To get the protein's UniProt ID, use the get_uniprot_id_by_protein_symbol tool first.
Args: protein_id (str): The protein identifier or accession (e.g., "P04637" or "CYC_HUMAN"). source_db (str, optional): The protein database source. Defaults to "uniprot". include_structure_info (bool, optional): Whether to include structural information. Defaults to False. species_filter (str, optional): Taxonomy ID to filter results (e.g., "9606" for human). Defaults to None.
Returns: dict: Protein domain information including InterPro matches, domain architecture, and optional structural data
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| include_structure_info | No | Whether to include structural information | |
| protein_id | Yes | The protein identifier/accession (e.g., 'P04637' or 'CYC_HUMAN') | |
| source_db | No | The protein database source ('uniprot', 'reviewed', or 'unreviewed') | uniprot |
| species_filter | No | Taxonomy ID to filter results (e.g., '9606' for human) |
Implementation Reference
- The primary handler function for the 'get_protein_domains' tool (prefixed as 'bc_get_protein_domains' in the main server). It queries the InterPro API to retrieve protein domains, matches, and optional structure info.@core_mcp.tool() def get_protein_domains( protein_id: Annotated[ str, Field(description="UniProt ID/accession (e.g., 'P04637' or 'CYC_HUMAN')"), ], source_db: Annotated[ str, Field(description="Database source ('uniprot', 'reviewed', or 'unreviewed')"), ] = "uniprot", include_structure_info: Annotated[ bool, Field(description="Include structural information"), ] = False, species_filter: Annotated[ Optional[str], Field(description="Taxonomy ID filter (e.g., '9606' for human)"), ] = None, ) -> dict: """Get protein domain architecture and InterPro matches. Returns all InterPro domains, functional sites, and domain architecture. Returns: dict: Protein metadata with interpro_matches array, interpro_match_count, domain_architecture, optionally structure data or error message. """ base_url = f"https://www.ebi.ac.uk/interpro/api/protein/{source_db}/{protein_id}" # Build query parameters params = {} extra_fields = ["description", "sequence"] if include_structure_info: extra_fields.append("structure") if species_filter: params["tax_id"] = species_filter params["extra_fields"] = ",".join(extra_fields) try: # Get protein information with InterPro matches response = requests.get(base_url, params=params) response.raise_for_status() protein_data = response.json() if not protein_data.get("metadata"): return {"error": f"No data found for protein {protein_id}"} result = protein_data["metadata"] # Get InterPro domain matches for this protein try: domains_url = f"https://www.ebi.ac.uk/interpro/api/entry/interpro/protein/{source_db}/{protein_id}" domains_response = requests.get(domains_url) if domains_response.status_code == 200: domains_data = domains_response.json() result["interpro_matches"] = domains_data.get("results", []) result["interpro_match_count"] = len(domains_data.get("results", [])) else: result["interpro_matches"] = [] result["interpro_match_count"] = 0 except Exception as e: result["interpro_matches"] = {"error": f"Could not fetch InterPro matches: {e}"} # Get domain architecture ID (IDA) if available try: ida_url = f"{base_url}?ida" ida_response = requests.get(ida_url) if ida_response.status_code == 200: ida_data = ida_response.json() if ida_data.get("metadata", {}).get("ida"): result["domain_architecture"] = ida_data["metadata"]["ida"] except Exception: pass # IDA is optional return result except requests.exceptions.HTTPError as e: if e.response.status_code == 404: return {"error": f"Protein {protein_id} not found in {source_db}"} return {"error": f"HTTP error: {e}"} except Exception as e: return {"error": f"Exception occurred: {e!s}"}
- src/biocontext_kb/core/_server.py:1-7 (registration)Defines the core_mcp FastMCP server instance named 'BC', where the @tool() decorated functions like get_protein_domains are automatically registered.from fastmcp import FastMCP core_mcp = FastMCP( # type: ignore "BC", instructions="Provides access to biomedical knowledge bases.", )
- src/biocontext_kb/app.py:35-40 (registration)Registers the core_mcp server (containing get_protein_domains) into the main 'BioContextAI' MCP app with prefix 'bc' (slugify('BC')), making the tool available as 'bc_get_protein_domains'.for mcp in [core_mcp, *(await get_openapi_mcps())]: await mcp_app.import_server( mcp, slugify(mcp.name), ) logger.info("MCP server setup complete.")
- Pydantic schema definitions for the tool inputs using Annotated and Field, including descriptions.def get_protein_domains( protein_id: Annotated[ str, Field(description="UniProt ID/accession (e.g., 'P04637' or 'CYC_HUMAN')"), ], source_db: Annotated[ str, Field(description="Database source ('uniprot', 'reviewed', or 'unreviewed')"), ] = "uniprot", include_structure_info: Annotated[ bool, Field(description="Include structural information"), ] = False, species_filter: Annotated[ Optional[str], Field(description="Taxonomy ID filter (e.g., '9606' for human)"), ] = None, ) -> dict:
- Imports the get_protein_domains handler for exposure in the interpro module.from ._get_protein_domains import get_protein_domains