BioContextAI Knowledgebase MCP

Instructions

Implementation Reference

• src/biocontext_kb/core/openfda/_advanced_search.py:9-54 (handler)

  The core handler function for the 'get_available_pharmacologic_classes' tool. It is decorated with @core_mcp.tool() for MCP registration and implements the logic to query the OpenFDA API for unique pharmacologic classes based on class_type (epc, moa, pe, cs), returning available classes with counts.

  @core_mcp.tool()
  def get_available_pharmacologic_classes(
      class_type: Annotated[
          str,
          Field(
              description="Class type: 'epc' (Established Pharmacologic Class), 'moa' (Mechanism of Action), 'pe' (Physiologic Effect), or 'cs' (Chemical Structure)"
          ),
      ] = "epc",
      limit: Annotated[int, Field(description="Number of unique classes to return", ge=1, le=1000)] = 100,
  ) -> dict:
      """Get available pharmacologic classes from FDA database. Call this first to see available options.
  
      Returns:
          dict: Class type, field, available_classes array with term/count, total_found or error message.
      """
      # Map class type to the appropriate OpenFDA field
      class_field_mapping = {
          "epc": "openfda.pharm_class_epc",  # Established Pharmacologic Class
          "moa": "openfda.pharm_class_moa",  # Mechanism of Action
          "pe": "openfda.pharm_class_pe",  # Physiologic Effect
          "cs": "openfda.pharm_class_cs",  # Chemical Structure
      }
  
      if class_type.lower() not in class_field_mapping:
          return {"error": "class_type must be one of: epc, moa, pe, cs"}
  
      field = class_field_mapping[class_type.lower()]
  
      # Use the count endpoint to get unique values
      base_url = "https://api.fda.gov/drug/drugsfda.json"
      params: Any = {"count": field, "limit": limit}
  
      try:
          response = requests.get(base_url, params=params)
          response.raise_for_status()
          data = response.json()
  
          return {
              "class_type": class_type,
              "field": field,
              "available_classes": data.get("results", []),
              "total_found": len(data.get("results", [])),
          }
      except requests.exceptions.RequestException as e:
          return {"error": f"Failed to fetch available pharmacologic classes: {e!s}"}

• src/biocontext_kb/core/openfda/__init__.py:1-19 (registration)

  The openfda module __init__.py exports the get_available_pharmacologic_classes function, making it available for import and use in tool registration contexts.

  from ._advanced_search import (
      get_available_pharmacologic_classes,
      get_generic_equivalents,
      search_drugs_by_therapeutic_class,
  )
  from ._count_drugs import count_drugs_by_field, get_drug_statistics
  from ._get_drug_info import get_drug_by_application_number, get_drug_label_info
  from ._search_drugs import search_drugs_fda
  
  __all__ = [
      "count_drugs_by_field",
      "get_available_pharmacologic_classes",
      "get_drug_by_application_number",
      "get_drug_label_info",
      "get_drug_statistics",
      "get_generic_equivalents",
      "search_drugs_by_therapeutic_class",
      "search_drugs_fda",
  ]

• src/biocontext_kb/core/openfda/_advanced_search.py:10-18 (schema)

  Pydantic schema definitions for input parameters: class_type (str, default 'epc') and limit (int, 1-1000, default 100), with detailed descriptions and constraints.

  def get_available_pharmacologic_classes(
      class_type: Annotated[
          str,
          Field(
              description="Class type: 'epc' (Established Pharmacologic Class), 'moa' (Mechanism of Action), 'pe' (Physiologic Effect), or 'cs' (Chemical Structure)"
          ),
      ] = "epc",
      limit: Annotated[int, Field(description="Number of unique classes to return", ge=1, le=1000)] = 100,
  ) -> dict: