Automated End-to-End test scripts are inherently fragile. Modifications to the User Interface (UI) cause automation test script failures, imposing significant maintenance overhead. Automated test script repair using Large Language Model (LLM) has shown promise, but existing approaches operate without real-time access to the application under test. To the best of our knowledge, no prior controlled study has compared LLM-based test-script repair with and without MCP-mediated live browser access while keeping the remaining repair settings consistent. Through a controlled experiment on a web application, we inject 30 failure scenarios across two categories of UI modifications (locator changes and DOM structural changes) and evaluate two LLM models (GPT 5.0 Mini and Claude Haiku 4.5) with two conditions (with and without MCP access). Configurations with MCP achieve a correct patch rate of 65%, compared with 25% without MCP. The plausible patch rate reached 98% (vs. 87%), the failure rate dropped from 13.3% to 1.7%, and MTTR decreased by 31 seconds. These results suggest that providing agents with MCP-mediated live browser access primarily enhances repair correctness rather than merely increasing re-execution success rates.