Claude, a Large Language Model, utilizes two distinct context management methods: memory and the Model Context Protocol (MCP), each serving different purposes to enhance user interactions. Memory allows Claude to retain user preferences and context across sessions, thus providing continuity by remembering details such as preferred programming languages and response styles. This persistence makes it ideal for long-term projects where continuity is essential. In contrast, MCP offers real-time access to external data sources like documentation and APIs, ensuring responses are current by retrieving specific information during a session. This makes MCP suitable for scenarios requiring up-to-date data, like customer support involving frequently updated API documentation. For optimal performance, both memory and MCP rely on well-structured documentation, which should include clear hierarchies, metadata, and consistent formatting to facilitate accurate and efficient data retrieval. By combining memory and MCP, Claude delivers personalized and precise responses, contingent on the quality and structure of the provided documentation.