Nuanced MCP Server

Instructions

Implementation Reference

• nuanced_mcp_server.py:107-154 (handler)

  The core handler function for the 'get_function_call_graph' tool, decorated with @mcp.tool(). It determines the repository, enriches the code graph for the specified function, handles errors, and formats the output using a helper function.
  @mcp.tool() def get_function_call_graph(file_path: str, function_name: str, repo_path: str = None) -> str: """Get the call graph for a specific function. Args: file_path: Path to the file containing the function function_name: Name of the function to analyze repo_path: Optional repository path (uses active repository if not specified) Returns: Information about the function's call graph """ global _code_graphs, _active_repo # Determine which repository to use target_repo = repo_path if target_repo: target_repo = os.path.abspath(target_repo) if target_repo not in _code_graphs: return f"Error: Repository '{repo_path}' not initialized" else: if _active_repo is None: return "Error: No active repository. Please initialize a graph first." target_repo = _active_repo code_graph = _code_graphs[target_repo] try: # Resolve relative paths to absolute if not os.path.isabs(file_path): file_path = os.path.join(target_repo, file_path) # Get enrichment result enrichment = code_graph.enrich(file_path, function_name) if enrichment.errors: error_messages = [str(error) for error in enrichment.errors] return f"Errors retrieving call graph:\n" + "\n".join(error_messages) if not enrichment.result: return f"Function '{function_name}' not found in '{file_path}'" # Format the result for better readability result = format_enrichment_result(file_path, function_name, enrichment.result) return result except Exception as e: return f"Error retrieving call graph: {str(e)}"
• nuanced_mcp_server.py:487-555 (helper)

  Helper function used by the handler to format the enrichment result from CodeGraph.enrich into a readable markdown string with function info, direct calls, callers, and full JSON subgraph.
  def format_enrichment_result( file_path: str, function_name: str, subgraph: Dict[str, Any] ) -> str: """Format the enrichment result for better readability""" # Find the entry point node key entrypoint_keys = [k for k in subgraph.keys() if k.endswith(function_name)] if not entrypoint_keys: return f"Error: Entry point function {function_name} not found in subgraph" entrypoint_key = entrypoint_keys[0] entrypoint_node = subgraph[entrypoint_key] # Extract direct callees direct_callees = entrypoint_node.get("callees", []) direct_callee_names = [path.split(".")[-1] for path in direct_callees] # Get callers (functions that call this function) # This requires iterating through all nodes in the graph callers = [] for node_key, node in subgraph.items(): if node_key == entrypoint_key: continue if entrypoint_key in node.get("callees", []): callers.append(node_key) caller_names = [path.split(".")[-1] for path in callers] # Format the result result = [ f"## Function Call Graph for '{function_name}' in {file_path}", "", "### Function Information", f"- Full path: {entrypoint_key}", f"- Filepath: {entrypoint_node.get('filepath', 'Unknown')}", f"- Line number: {entrypoint_node.get('lineno', 'Unknown')}", "", "### Direct Function Calls", ] if direct_callee_names: for name in direct_callee_names: result.append(f"- {name}") else: result.append("- No direct function calls found") result.extend( [ "", "### Called By", ] ) if caller_names: for name in caller_names: result.append(f"- {name}") else: result.append("- Not called by any other functions in the analyzed code") result.extend( [ "", "### Full Call Graph (JSON)", "```json", json.dumps(subgraph, indent=2), "```", ] ) return "\n".join(result)