CLI vs MCP: which API interface should you build first? (June 2026)

In the exploration of AI agents accessing APIs, the choice between process-based command-line interfaces (CLI) and protocol-based Model Context Protocol (MCP) is crucial, as each serves distinct operational needs. CLIs, which are process-based, execute tasks by spawning subprocesses without maintaining persistent connections or schemas, making them suitable for isolated, single-step tasks. On the other hand, MCP, introduced by Anthropic in 2024, uses a JSON-RPC protocol to maintain stateful sessions with schema validation, making it ideal for complex, multi-step workflows requiring shared context and rigorous security measures. While CLIs offer immediate usability due to AI models' pre-existing familiarity with them and incur fewer token costs for single calls, they lack the session persistence and detailed audit trails that MCP provides, which are crucial for tasks involving many sequential calls. The decision between CLI and MCP should consider factors like task complexity, the need for session persistence, authentication requirements, and the AI model's familiarity with the interface, as well as the organization's infrastructure and compliance needs. Fern enables teams to generate both CLIs and MCP servers from API specifications, allowing flexibility in serving AI agents without rebuilding interfaces.