Another CLI? What Makes It Different from Ollama's Built-In
Another CLI? What Makes It Different from Ollama's Built-In
Fair question. Ollama already has a CLI. You can run ollama run llama3 and start chatting. Why would you need another command-line tool on top of that?
What Ollama's CLI Does Well
Ollama is excellent at model management - pulling, running, and serving models locally. The built-in chat interface works for quick questions. The API server is solid for integrations. If all you need is to run inference against a local model, Ollama's CLI is all you need.
Where a Dedicated Agent CLI Differs
The gap shows up when you want the model to actually do things on your computer. Ollama's CLI is a conversation interface. A desktop agent CLI is an execution interface.
The differences come down to three things. First, tool calling - the agent CLI connects to MCP servers that give the model access to your filesystem, browser, apps, and system APIs. Ollama's CLI just generates text. Second, persistent memory - the agent remembers what you worked on last session, knows your preferences, and builds context over time. Third, desktop integration - the agent can read your screen, click buttons, fill forms, and navigate apps through the accessibility API.
The Right Mental Model
Think of Ollama as the engine and the agent CLI as the car. You need the engine, but the engine alone does not get you anywhere. The agent CLI adds the steering wheel, pedals, and navigation system that turn raw inference into useful automation.
You can use both together. Run your models through Ollama's server, and point your agent CLI at the local API endpoint. You get Ollama's model management with the agent's execution capabilities. Best of both worlds.
The question is not "which CLI" - it is "what do you want the model to do?" If the answer is just chat, Ollama's CLI is fine. If the answer involves controlling your computer, you need something more.
Fazm is an open source macOS AI agent. Open source on GitHub.