MCP: Programmatic Tool Calling (Code Mode) with OpenSandbox

Introduction Model Context Protocol or MCP enables AI agents to access external systems they cannot reach by default, including authenticated APIs, CI/CD pipelines, live process streams, and IDE integrations. It acts as a structured bridge between the model and real-world environments, allowing controlled interaction with tools and infrastructure. However, MCP does not automatically make interactions efficient or intelligent. Traditional MCP implementations often inject large JSON payloads into the model context, which increases token consumption and reduces efficiency. MCP also does not eliminate the need for proper tool selection and orchestration; if poorly structured, it can introduce unnecessary abstraction and overhead. In environments where agents can directly execute commands or interact with systems natively, MCP may become redundant, as it primarily serves as an access layer rather than an execution engine. In many software products, having hundreds of APIs is normal. With a