Noctua MCP Server

Instructions

# Check if a model is empty
result = model_summary("gomodel:new_empty_model")
if result["individual_count"] == 0:
    print("Model is empty")

# Analyze model complexity
result = model_summary("gomodel:12345")
causal_edges = result["predicate_distribution"].get("RO:0002411", 0)
causal_edges += result["predicate_distribution"].get("RO:0002413", 0)  # provides input for
causal_edges += result["predicate_distribution"].get("RO:0002629", 0)  # directly positively regulates
causal_edges += result["predicate_distribution"].get("RO:0002630", 0)  # directly negatively regulates
print(f"Model has {causal_edges} causal relationships")

Implementation Reference

• src/noctua_mcp/mcp_server.py:1186-1268 (handler)

  The handler function for the 'model_summary' tool. It fetches the GO-CAM model using BaristaClient.get_model(), then computes summary statistics: number of individuals, facts, model state, and a distribution of predicates used in facts.

  @mcp.tool()
  async def model_summary(model_id: str) -> Dict[str, Any]:
      """
      Get a summary of a GO-CAM model including counts and key information.
  
      Args:
          model_id: The GO-CAM model identifier
  
      Returns:
          Summary with individual count, fact count, and predicate distribution
  
      Examples:
          # Get summary of a model
          result = model_summary("gomodel:5fce9b7300001215")
          # Returns:
          # {
          #   "model_id": "gomodel:5fce9b7300001215",
          #   "state": "production",
          #   "individual_count": 42,
          #   "fact_count": 67,
          #   "predicate_distribution": {
          #     "RO:0002333": 15,  # enabled_by (note: not in vetted list)
          #     "RO:0002411": 8,   # causally upstream of
          #     "BFO:0000066": 12,  # occurs_in
          #     "BFO:0000050": 5    # part_of
          #   }
          # }
  
          # Check if a model is empty
          result = model_summary("gomodel:new_empty_model")
          if result["individual_count"] == 0:
              print("Model is empty")
  
          # Analyze model complexity
          result = model_summary("gomodel:12345")
          causal_edges = result["predicate_distribution"].get("RO:0002411", 0)
          causal_edges += result["predicate_distribution"].get("RO:0002413", 0)  # provides input for
          causal_edges += result["predicate_distribution"].get("RO:0002629", 0)  # directly positively regulates
          causal_edges += result["predicate_distribution"].get("RO:0002630", 0)  # directly negatively regulates
          print(f"Model has {causal_edges} causal relationships")
      """
      client = get_client()
      resp = client.get_model(model_id)
  
      if resp.validation_failed:
          return {
              "success": False,
              "error": "Validation failed",
              "reason": resp.validation_reason,
              "model_id": model_id
          }
  
      if resp.error:
          return {
              "success": False,
              "error": "Failed to retrieve model",
              "reason": resp.error,
              "model_id": model_id
          }
  
      # Extract summary information
      individuals = resp.individuals
      facts = resp.facts
  
      # Count predicates
      predicate_counts: Dict[str, int] = {}
      for fact in facts:
          # fact is now a Pydantic Fact object, not a dict
          pred = fact.property if hasattr(fact, 'property') else "unknown"
          predicate_counts[pred] = predicate_counts.get(pred, 0) + 1
  
      # Get model state if available
      model_state = resp.model_state
  
      return {
          "success": True,
          "model_id": model_id,
          "state": model_state,
          "individual_count": len(individuals),
          "fact_count": len(facts),
          "predicate_distribution": predicate_counts,
      }

• src/noctua_mcp/mcp_server.py:56-62 (helper)

  Helper function to lazily initialize and return the shared BaristaClient instance used by model_summary and other tools.

  def get_client() -> BaristaClient:
      """Get or create the Barista client instance."""
      global _client
      if _client is None:
          _client = BaristaClient()
      return _client

• src/noctua_mcp/mcp_server.py:1186-1186 (registration)

  FastMCP tool registration decorator for the model_summary handler.

  @mcp.tool()