refactor: Move McpError import to module level

Address review feedback from @seratch and Copilot AI.

Previously, McpError was imported inside the exception handler on
every tool invocation error, causing repeated import overhead.

This change moves the import to module level with proper fallback
for Python < 3.10 (where mcp package is not available).

Author: gn00295120

src/agents/mcp/util.py

@@ -15,6 +15,14 @@
 from ..tracing import FunctionSpanData, get_current_span, mcp_tools_span
 from ..util._types import MaybeAwaitable
 
+# Import McpError if available (requires Python >= 3.10)
+# This allows us to distinguish MCP HTTP errors from programming errors.
+# See: https://github.com/openai/openai-agents-python/issues/879
+try:
+    from mcp.shared.exceptions import McpError
+except ImportError:
+    McpError = None  # type: ignore
+
 if TYPE_CHECKING:
     from mcp.types import Tool as MCPTool
 
@@ -206,19 +214,13 @@ async def invoke_mcp_tool(
             # by returning a structured error response instead of crashing the run.
             # This allows the agent to handle the error and decide how to respond.
             # See: https://github.com/openai/openai-agents-python/issues/879
-            try:
-                from mcp.shared.exceptions import McpError
-
-                if isinstance(e, McpError):
-                    # This is an HTTP error from upstream service - return structured error
-                    logger.warning(f"MCP tool {tool.name} encountered upstream error: {e}")
-                    error_response = {
-                        "error": {"message": str(e), "tool": tool.name, "type": "upstream_error"}
-                    }
-                    return json.dumps(error_response)
-            except ImportError:
-                # MCP not available (Python < 3.10), fall through to original behavior
-                pass
+            if McpError is not None and isinstance(e, McpError):
+                # This is an HTTP error from upstream service - return structured error
+                logger.warning(f"MCP tool {tool.name} encountered upstream error: {e}")
+                error_response = {
+                    "error": {"message": str(e), "tool": tool.name, "type": "upstream_error"}
+                }
+                return json.dumps(error_response)
 
             # For other exceptions (programming errors, etc.), raise as before
             logger.error(f"Error invoking MCP tool {tool.name}: {e}")