Building efficient AI agents with GraphQL and the Apollo MCP Server involves managing token usage within the context window, which directly affects costs, latency, and agent capabilities. GraphQL addresses the inefficiencies of traditional REST APIs by allowing precise data querying, which minimizes unnecessary token consumption. Apollo's MCP Server facilitates this by integrating GraphQL operations as MCP tools without manual definitions, enabling seamless iteration and deployment. This approach allows developers to optimize token usage by focusing on relevant inputs and outputs, reducing unnecessary data processing and improving AI agent efficiency. Additionally, GraphQL's features, such as aliases and field selection, empower developers to tailor data interactions, ensuring clarity and reducing token expenditure, ultimately enhancing the user experience by allowing longer, more cost-effective conversations with AI agents.