bc_get_efo_id_by_disease_name
Find EFO/Mondo/HP IDs for diseases to use in Open Targets queries by searching the OLS ontology with a disease name.
Instructions
Search OLS for EFO/Mondo/HP IDs related to a disease name. Use this to get EFO IDs for Open Targets queries.
Returns: dict: EFO IDs with efo_ids array containing id, label, description or error message.
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| disease_name | Yes | Disease name to search for (e.g., 'choledocholithiasis') | |
| size | No | Maximum number of results to return | |
| exact_match | No | Whether to perform exact match search |
Output Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Implementation Reference
- The handler function for the 'bc_get_efo_id_by_disease_name' tool. It queries the OLS API (EBI) to retrieve EFO, MONDO, or HP ontology IDs matching the given disease name. Includes input schema via Pydantic Annotated fields and handles errors gracefully.
@core_mcp.tool() def get_efo_id_by_disease_name( disease_name: Annotated[str, Field(description="Disease name to search for (e.g., 'choledocholithiasis')")], size: Annotated[ int, Field(description="Maximum number of results to return"), ] = 5, exact_match: Annotated[ bool, Field(description="Whether to perform exact match search"), ] = False, ) -> Dict[str, Any]: """Search OLS for EFO/Mondo/HP IDs related to a disease name. Use this to get EFO IDs for Open Targets queries. Returns: dict: EFO IDs with efo_ids array containing id, label, description or error message. """ if not disease_name: return {"error": "disease_name must be provided"} url = "https://www.ebi.ac.uk/ols4/api/v2/entities" params = { "search": disease_name, "size": str(size), "lang": "en", "exactMatch": str(exact_match).lower(), "includeObsoleteEntities": "false", "ontologyId": "efo", } def starts_with_valid_prefix(curie: str) -> bool: """Check if the curie starts with a valid prefix.""" return any(curie.startswith(prefix) for prefix in ["EFO:", "MONDO:", "HP:"]) try: response = requests.get(url, params=params) response.raise_for_status() data = response.json() # Check that at least one item is in elements and that appearsIn includes EFO if not data.get("elements") or not any( starts_with_valid_prefix(str(element.get("curie", ""))) for element in data["elements"] ): return {"error": "No results found"} # Extract EFO IDs and their labels efo_ids = [ { "id": element["curie"].replace(":", "_"), "label": element["label"], "description": element.get("description", ""), } for element in data["elements"] if starts_with_valid_prefix(str(element.get("curie", ""))) ] return {"efo_ids": efo_ids} except requests.exceptions.RequestException as e: return {"error": f"Failed to fetch EFO IDs: {e!s}"} - src/biocontext_kb/core/_server.py:3-6 (registration)Definition of core_mcp FastMCP instance with 'BC' prefix, used by @core_mcp.tool() decorator to register tools with 'bc_' prefix (e.g., bc_get_efo_id_by_disease_name).
core_mcp = FastMCP( # type: ignore "BC", instructions="Provides access to biomedical knowledge bases.", ) - src/biocontext_kb/app.py:36-39 (registration)Imports the core_mcp server (containing the tool) into the main BioContextAI MCP app, making the tool available.
await mcp_app.import_server( mcp, slugify(mcp.name), ) - Pydantic schema definitions for tool inputs using Annotated and Field.
disease_name: Annotated[str, Field(description="Disease name to search for (e.g., 'choledocholithiasis')")], size: Annotated[ int, Field(description="Maximum number of results to return"), ] = 5, exact_match: Annotated[ bool, Field(description="Whether to perform exact match search"), ] = False, ) -> Dict[str, Any]: